{ "schemaVersion": 1, "name": "BotSpot", "baseUrl": "https://botspot.trade", "artifacts": { "manifest": "https://botspot.trade/.well-known/botspot-manifest.json", "llms": "https://botspot.trade/llms.txt", "openapi": "https://botspot.trade/openapi.json", "sitemap": "https://botspot.trade/sitemap.xml", "blogSitemap": "https://botspot.trade/blog/sitemap.xml", "developerDocs": "https://botspot.trade/agents", "mcp": "https://botspot.trade/.well-known/mcp" }, "sourceContract": { "routeMetadata": "src/site/siteRoutes.js", "brokerConnections": "src/site/brokerConnectionSource.js", "publicPricing": "src/site/publicPricingSource.js", "dynamicPublicRoutes": "scripts/generate-site-artifacts.js --dynamic reads public blog, challenge, and marketplace APIs during production builds.", "note": "Generated artifacts and the broker connection UI share these sources. Do not hand-edit public artifacts." }, "routes": { "public": [ { "path": "/", "url": "https://botspot.trade/", "title": "AI Trading Bot Builder & Backtesting Platform | BotSpot", "description": "Turn your trading rules into a testable system. Build with AI, inspect historical evidence, and connect your broker with BotSpot.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": { "eyebrow": "BotSpot AI trading workspace", "heading": "Hire an AI agent to run your trading.", "summary": "Turn trading rules into inspectable code, run historical simulations, and connect a supported broker without giving BotSpot custody of your funds.", "sections": [ { "heading": "Build, backtest, and operate in one workspace", "paragraphs": [ "BotSpot is an AI trading-bot builder and backtesting platform. Describe entries, exits, sizing, and risk in plain English. The agent turns those rules into editable Lumibot strategy code you can read before anything runs.", "Historical simulations are labeled as simulated. They can include return, drawdown, trades, and logs for a date range you choose. A backtest is not live trading and does not guarantee future results.", "When you are ready, connect a supported brokerage account and approve paper or live operation. You keep funds at the broker. BotSpot does not take custody, and it does not place trades until you approve the run." ] }, { "heading": "What you can do after you start", "bullets": [ "Describe a strategy and inspect the generated code.", "Run a historical simulation and read trades, drawdown, and logs.", "Clone a public marketplace strategy and customize it in your account.", "Connect supported brokers for paper or live operation after you approve the settings.", "Use ChatGPT, Claude, Cursor, Codex, or another MCP client with the same BotSpot tools." ] }, { "heading": "Pricing without invented offers", "paragraphs": [ "Public BotSpot software plans start at the Light subscription and scale through Starter, Pro, and All Access. Current advertised software prices are published on the pricing page and in the public pricing source. Business capacity is quoted separately. Education products are separate paid offers.", "BotSpot core software is paid upfront. This page does not advertise a free product trial. Capturing an email is not a substitute for a paid plan." ] }, { "heading": "Risk", "paragraphs": [ "Automated trading can lose money. Simulated backtests, paper trading, and past live history do not guarantee future performance. BotSpot is software for automating rules you inspect. It is not an investment adviser and does not promise returns." ] } ], "relatedLinks": [ { "label": "See BotSpot plans", "url": "/pricing" }, { "label": "Browse marketplace strategies", "url": "/marketplace" }, { "label": "MCP for Agents", "url": "/agents" }, { "label": "OAuth authorization server metadata", "url": "https://mcp.botspot.trade/.well-known/oauth-authorization-server" }, { "label": "OAuth protected resource and scopes", "url": "https://mcp.botspot.trade/.well-known/oauth-protected-resource" } ] }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/sales", "url": "https://botspot.trade/sales", "title": "Build AI Trading Bots in Minutes | BotSpot", "description": "Build, backtest, and deploy automated trading strategies with AI. Start without coding and connect your existing brokerage account.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": { "eyebrow": "Start with BotSpot", "heading": "Build AI trading bots in minutes", "summary": "Create an account, describe a trading idea, inspect the generated strategy, and backtest it before you connect a broker.", "sections": [ { "heading": "From a prompt to an inspectable bot", "paragraphs": [ "BotSpot is for people who want their own rules running at their own broker. You describe the idea. The AI Agent drafts strategy code you can read. You run a historical simulation, review trades and drawdown, and only then decide whether to connect a supported account.", "The sales path is the paid-upfront BotSpot software purchase. It is not a free trading product, a signal service that hides the rules, or a promise that a generated bot will profit." ] }, { "heading": "What you keep control of", "bullets": [ "Strategy code and revisions in your account.", "Backtest date range, logs, and simulated metrics.", "Broker connection, paper versus live mode, and start approval.", "Risk limits you set before a bot is allowed to run." ] }, { "heading": "Risk", "paragraphs": [ "Trading involves risk of loss. Backtests are simulations. Paper trading is not live trading. BotSpot does not guarantee returns." ] } ], "relatedLinks": [ { "label": "Compare plans", "url": "/pricing" }, { "label": "Open the algorithm marketplace", "url": "/marketplace" }, { "label": "MCP for Agents", "url": "/agents" } ] }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/marketplace", "url": "https://botspot.trade/marketplace", "title": "Algorithm Marketplace: AI Trading Strategies | BotSpot", "description": "Browse public trading strategies with live history and backtest results, then clone a strategy and customize it in BotSpot.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": { "eyebrow": "Public strategy catalog", "heading": "Algorithm Marketplace", "summary": "Browse public BotSpot trading strategies, read each listing’s published rules and simulated metrics, then clone a strategy into your own account to inspect it.", "sections": [ { "heading": "A catalog of inspectable strategy templates", "paragraphs": [ "The BotSpot algorithm marketplace is a public catalog of trading-bot templates. Each listing can publish a title, description, asset classes, simulated backtest fields, and live history from connected bots. You open a listing, read what the publisher actually wrote, and clone the strategy into your account if you want to inspect the rules.", "Marketplace pages are not a ranking of “best bots,” a guaranteed-return leaderboard, or a managed-account shop. BotSpot does not invent equity curves for listings that omit them. If a listing has no drawdown or date range, that evidence is missing.", "Cloning copies the published strategy into your workspace. It does not start live trading. You still choose whether to simulate, whether to connect a broker, and whether to approve paper or live mode." ] }, { "heading": "How to read a listing without fooling yourself", "paragraphs": [ "Treat backtest CAGR, Sharpe, and max drawdown as historical simulations. When the listing includes a window, read the return next to that window and next to drawdown. A high simulated return with an unpublished drawdown is incomplete evidence.", "Live figures, when present, describe published connected-bot history for that listing. Live history can still lose money, can include different brokers and sizes, and is not a promise that your clone will match it.", "Use the listing description and details to understand entries, exits, sizing, and risk. If those fields are thin, clone the strategy and read the code rather than filling the gaps with marketing language." ], "bullets": [ "Prefer listings that publish rules, simulated drawdown, and a date range together.", "Label every backtest number as simulated when you discuss it.", "Do not treat marketplace sort order as investment advice.", "Run your own simulation after cloning before you consider live mode." ] }, { "heading": "What happens after you clone", "paragraphs": [ "In your BotSpot account you can revise the strategy, backtest it on dates you choose, and keep it stopped. Connecting a supported broker still requires your approval. Funds stay at the broker.", "Paid marketplace listings, when priced, are separate from BotSpot software plans. Software capacity for live bots, backtest hours, and AI revisions is described on the pricing page. This hub does not invent a listing price." ] }, { "heading": "Risk", "paragraphs": [ "Every marketplace strategy can lose money. Simulated results and past live history do not guarantee future performance. BotSpot is not an investment adviser. Use the catalog to inspect templates, not to outsource judgment." ] } ], "faq": [ { "question": "Are marketplace backtests live results?", "answer": "No. Backtest figures on marketplace listings are historical simulations. Live figures, when shown, are published connected-bot history for that listing. Neither is a guarantee of future results." }, { "question": "Does cloning a strategy start trading?", "answer": "No. Cloning copies the published strategy into your account so you can inspect and test it. Nothing trades until you connect a broker and approve a run." } ], "relatedLinks": [ { "label": "Compare BotSpot plans", "url": "/pricing" }, { "label": "Read backtesting metrics", "url": "/guides/backtesting-metrics-explained" }, { "label": "Algorithmic trading risk guide", "url": "/guides/algorithmic-trading-risk-management" } ] }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/sales-marketplace", "url": "https://botspot.trade/sales-marketplace", "title": "Find an Automated Trading Strategy | BotSpot", "description": "Explore ready-to-run trading strategies, review performance data, and choose a bot to customize and deploy through BotSpot.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": null, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/pricing", "url": "https://botspot.trade/pricing", "title": "AI Trading Bot Pricing & Plans | BotSpot", "description": "Compare BotSpot plans for AI strategy building, backtesting, live bots, broker connections, support, and trading education.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": { "eyebrow": "BotSpot plans", "heading": "AI trading bot pricing and plans", "summary": "Compare BotSpot software plans for AI strategy building, historical simulation hours, live bots, broker connections, and support.", "sections": [ { "heading": "Paid software capacity, published from one source", "paragraphs": [ "BotSpot software plans are paid subscriptions. Public prices for Light, Starter, Pro, and All Access come from the same pricing source used by this page and by generated site artifacts. Business capacity is custom. Education products are separate paid offers.", "Plans differ by live-bot capacity, backtesting hours, strategy revisions, AI credits, and support. They do not sell a guaranteed return. Backtests remain simulations on every plan." ] }, { "heading": "What you are paying for", "bullets": [ "AI Agent workflow to draft and revise inspectable strategy code.", "Historical simulation hours to review trades, drawdown, and logs.", "Capacity to run approved live bots at a supported broker.", "Marketplace access to clone public strategy templates.", "Support and Live Algo Lab access on higher plans as published on this page." ] }, { "heading": "Risk", "paragraphs": [ "Paying for software does not reduce market risk. Automated trading can lose money. BotSpot does not offer a free core SaaS plan on this page." ] } ], "relatedLinks": [ { "label": "Start with BotSpot", "url": "/sales" }, { "label": "Browse marketplace strategies", "url": "/marketplace" }, { "label": "Enterprise inquiries", "url": "/enterprise" } ] }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/enterprise", "url": "https://botspot.trade/enterprise", "title": "AI Solutions for Investment Firms | BotSpot", "description": "Diagnostic-led AI implementation for investment-firm growth, research, and senior-team capacity.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": null, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/agents", "url": "https://botspot.trade/agents", "title": "BotSpot MCP for Agents | ChatGPT, Claude, Codex & Gemini", "description": "Connect BotSpot to ChatGPT, Claude, Claude Code, Codex, Gemini CLI, Cursor, and other MCP clients for AI trading workflows.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": { "eyebrow": "BotSpot MCP", "heading": "MCP for Agents", "summary": "Use BotSpot from ChatGPT, Claude, Claude Code, Codex, Gemini CLI, Cursor, or another MCP-compatible client.", "sections": [ { "heading": "Visible setup guides for every supported client", "paragraphs": [ "Each client guide is published directly in the page instead of being hidden behind an interactive tab." ], "bullets": [ "ChatGPT connects to BotSpot through an OAuth app.", "Claude connects to BotSpot through a remote OAuth MCP connector.", "Claude Code connects to BotSpot with a local API key.", "Codex connects to BotSpot through its MCP configuration.", "Gemini CLI connects to BotSpot through Streamable HTTP and OAuth.", "Cursor connects to BotSpot through its MCP configuration." ] } ], "relatedLinks": [ { "label": "Create a BotSpot API key", "url": "/account-settings/api-keys" }, { "label": "Open the BotSpot AI Agent", "url": "/ai-agent" } ] }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/case-studies", "url": "https://botspot.trade/case-studies", "title": "Algorithmic Trading Case Studies | BotSpot", "description": "Explore complex backtests and practical examples of AI-assisted algorithmic trading workflows built with BotSpot.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": null, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/courses/ai-trading-bootcamp", "url": "https://botspot.trade/courses/ai-trading-bootcamp", "title": "AI Trading Course & Live Bootcamp | BotSpot", "description": "Learn AI trading with Claude, Codex and BotSpot in live sessions with Rob Grzesik. Build research workflows and trading agents. No coding required.", "image": "https://botspot.trade/images/courses/ai-trading-bootcamp-share.png", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": { "heading": "AI Trading Bootcamp", "summary": "Learn AI-assisted trading in a live, hands-on course with Rob Grzesik.", "sections": [ { "heading": "About this bootcamp", "paragraphs": [ "This is a live five-week bootcamp taught by Rob Grzesik, CEO of Lumiwealth BotSpot. He helped build Voyager into a billion-dollar crypto company, and he built technology at Greystone, a mortgage lender, that handled over $3 billion in transactions. He also has a Master of Finance, 25+ years of coding experience, and 15+ years in financial technology.", "You are not watching lecture videos. Each week you show up on Zoom for a hands-on class, build the workflow live, place a reviewed trade, and leave with a recording you can replay forever. You also join the community: work with other students, retake future classes, and keep new material we add going forward.", "Week one gets your AI trading workspace working: Claude, Codex, Cursor, BotSpot, market data, and your broker. You place your first stock or ETF trade the same night.", "Week two turns AI into a research desk that saves hours. You pull filings, financials, earnings, insider data, and news, then build scanners that surface the next candidates. Stop spending hours building watchlists. Stop guessing when you skip the work.", "Week three has two jobs. First, you learn Claude with TradingView to analyze charts and setups. Second, you learn to trade options, crypto, crypto futures, and prediction markets with AI doing the research and preparing the trades. Even if you are not an options trader yet, Claude, Codex, Cursor, or BotSpot can help you understand and build complex options trades.", "Week four turns a plain-English idea into a deterministic Python strategy you can read and trust. You backtest it, review the results, then iterate and improve. That is how you learn from the past before the same rules place trades without babysitting every click.", "Week five finishes with an AI trading agent you control. It can research, decide, and place trades on a schedule inside guardrails you set. When the cohort ends, that workspace keeps working for you.", "Plan on about one to two hours for each live Zoom call, plus about one to two hours of practice between sessions on your own setup with the prompts and checklists from class.", "You also get lifetime access, so you can retake later cohorts, keep new material we add, and join the optional five-week trading competition if you want a shared scoreboard. Real money is encouraged. The front door is using AI to research, review, and trade with control." ] } ], "relatedLinks": [ { "label": "View the recorded course", "url": "/courses/ai-trading-bootcamp/self-paced" } ] }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/courses/ai-trading-bootcamp/self-paced", "url": "https://botspot.trade/courses/ai-trading-bootcamp/self-paced", "title": "Self-Paced AI Bot Builder Bootcamp | BotSpot", "description": "Completed AI Bot Builder Bootcamp recordings on your schedule. Learn vibe coding, bot building, backtesting, broker deployment, crypto, options, and futures.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": null, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/challenges", "url": "https://botspot.trade/challenges", "title": "Free AI Trading Challenges | BotSpot", "description": "Join free live BotSpot AI trading challenges, build one practical workflow with Rob, and review your work before choosing the full bootcamp.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": { "eyebrow": "Free live education", "heading": "Free AI Trading Challenges", "summary": "Build one useful AI trading workflow during a live kickoff, improve it over seven days, then bring it to the live wrap-up for review.", "sections": [ { "heading": "How each challenge works", "paragraphs": [ "Current public challenge dates and registration links come from BotSpot live session data. Each challenge keeps its own canonical page so schedules and recordings remain findable." ], "bullets": [ "Join a live kickoff with Rob.", "Improve one practical project during the week.", "Bring your work to the live wrap-up for review." ] } ], "relatedLinks": [ { "label": "Explore the AI Trading Bootcamp", "url": "/courses/ai-trading-bootcamp" } ] }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/live-algo-lab", "url": "https://botspot.trade/live-algo-lab", "title": "Live Algorithmic Trading Lab | BotSpot", "description": "Join live weekly sessions covering real BotSpot workflows, algorithmic trading builds, strategy reviews, and implementation Q&A.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": null, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/upgrade-to-pro", "url": "https://botspot.trade/upgrade-to-pro", "title": "BotSpot Pro: More Bots, Backtests & Support", "description": "Upgrade BotSpot for higher strategy revision limits, more live bots, additional backtesting capacity, and priority support.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": null, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/help", "url": "https://botspot.trade/help", "title": "BotSpot Help & Support", "description": "Find BotSpot setup guidance, product help, broker connection information, and support resources.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": null, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/about", "url": "https://botspot.trade/about", "title": "About BotSpot | AI Trading Platform by Lumiwealth", "description": "Learn what BotSpot does, who operates it, how customer control works, and what its trading software does not promise.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": { "eyebrow": "About BotSpot", "heading": "Trading automation you can inspect and control", "summary": "BotSpot is an AI trading platform operated by Lumiwealth, Inc., a Delaware corporation.", "sections": [ { "heading": "What BotSpot does", "paragraphs": [ "BotSpot helps customers turn explicit trading rules into editable strategy code, test those rules against historical data, and connect supported brokerage accounts for paper or live operation. Customers can inspect generated code, backtest trades, drawdown, logs, and assumptions before deciding whether to run anything. BotSpot also provides an MCP server so supported AI clients can use the same account tools through documented authentication and scoped permissions.", "BotSpot does not hold customer cash or securities. Funds remain at the customer’s broker. BotSpot provides software and connectivity; it is not a broker-dealer or investment adviser, and it does not promise returns. Backtests and paper trading are simulations, while live trading can lose money because of market movement, slippage, liquidity, fees, connectivity, broker rules, and software behavior." ] }, { "heading": "Who operates BotSpot", "paragraphs": [ "Lumiwealth, Inc. operates BotSpot and publishes its current legal terms and privacy practices on this site. Product plans are paid upfront; BotSpot does not advertise a free product trial. Public pages describe available software, education, marketplace, broker, and agent-integration workflows without inventing performance or access claims." ] } ], "relatedLinks": [ { "label": "MCP for Agents", "url": "/agents" }, { "label": "BotSpot Terms of Service", "url": "/terms" }, { "label": "BotSpot Privacy Policy", "url": "/privacy" }, { "label": "Contact BotSpot", "url": "/contact" } ] }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/contact", "url": "https://botspot.trade/contact", "title": "Contact BotSpot | Product Support and Business Inquiries", "description": "Contact BotSpot for product support, account questions, MCP integrations, partnerships, enterprise services, and general inquiries.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": { "eyebrow": "Contact BotSpot", "heading": "Reach the team responsible for BotSpot", "summary": "Use the channel that matches your question so account, product, and business requests reach the right context.", "sections": [ { "heading": "Product and account support", "paragraphs": [ "For product setup, account access, billing, broker connections, backtests, deployments, marketplace listings, or MCP integration questions, email support@lumiwealth.com from the address associated with your BotSpot account when possible. Never include passwords, broker secrets, private keys, full API keys, payment-card details, or other authentication credentials in email.", "Email is not a trading control. Do not use email to place, change, or cancel an order, stop a live strategy, or report an urgent brokerage problem. Use BotSpot’s visible account controls for BotSpot automation and contact your broker directly for urgent order, position, funding, custody, or market-access issues." ] }, { "heading": "General and business inquiries", "paragraphs": [ "For partnerships, enterprise services, media, education, or other general questions, email contact@botspot.trade. BotSpot is operated by Lumiwealth, Inc. Product terms, privacy practices, risk disclosures, agent setup, pricing, and supported broker information remain available through public pages linked below so people and automated agents can verify current published claims before contacting the team." ] } ], "relatedLinks": [ { "label": "Email product support", "url": "mailto:support@lumiwealth.com" }, { "label": "Email BotSpot", "url": "mailto:contact@botspot.trade" }, { "label": "MCP for Agents", "url": "/agents" }, { "label": "BotSpot Privacy Policy", "url": "/privacy" } ] }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/terms", "url": "https://botspot.trade/terms", "title": "Terms of Service | BotSpot", "description": "Read BotSpot terms covering platform use, broker connections, marketplace content, AI outputs, fees, and trading risk.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": null, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/privacy", "url": "https://botspot.trade/privacy", "title": "Privacy Policy | BotSpot", "description": "Read how BotSpot collects, uses, protects, and shares information when you use its websites, applications, and services.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": null, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/blog", "url": "https://botspot.trade/blog", "title": "AI Trading & Market Automation Blog | BotSpot", "description": "Read BotSpot market newsletters, automated trading tutorials, AI strategy guides, and product updates.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": null, "content": { "eyebrow": "BotSpot writing", "heading": "Latest BotSpot articles", "summary": "Read BotSpot market newsletters, automated trading tutorials, AI strategy guides, and product updates.", "sections": [ { "heading": "What this blog publishes", "paragraphs": [ "The BotSpot blog collects product updates, automation tutorials, and market notes written for people who build and operate trading bots. Articles are editorial pages, not personalized investment advice.", "When a post discusses backtests, treat those figures as simulations unless the article clearly describes live history, including date range and drawdown. Nothing on the blog guarantees future returns." ] }, { "heading": "How to use the archive", "bullets": [ "Open an article for the full canonical URL under /blog/{slug}.", "Use tutorials alongside the in-app AI Agent and backtest workspace.", "Use product updates to see current workflow changes, then confirm behavior in the app." ] } ], "relatedLinks": [ { "label": "Open the AI Agent", "url": "/ai-agent" }, { "label": "Algorithm marketplace", "url": "/marketplace" }, { "label": "Trading guides", "url": "/guides" } ] }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/blog/using-ai-to-make-ai-profitable-swing-trading-bot-in-seconds", "url": "https://botspot.trade/blog/using-ai-to-make-ai-profitable-swing-trading-bot-in-seconds", "title": "Using AI to Make a Profitable Swing Trading Bot in Seconds", "description": "Step-by-step guide to create, backtest, and deploy a swing trading bot with AI.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": null, "content": null, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides", "url": "https://botspot.trade/guides", "title": "AI Trading and Backtesting Guides | BotSpot", "description": "Explore practical BotSpot guides for building AI trading strategies, backtesting evidence, controlling risk, connecting brokers, and using MCP clients.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "website", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "BotSpot trading guides", "heading": "Build, test, connect, and operate trading strategies", "summary": "Follow focused guides for choosing a workflow, turning rules into inspectable code, testing historical evidence, controlling deployment risk, and connecting ChatGPT, Claude, or Codex to supported broker workflows.", "primaryAction": { "label": "Start building in BotSpot", "url": "/ai-agent" }, "secondaryAction": { "label": "Compare trading platforms", "url": "/compare" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "Choose a guide by the decision you need to make", "paragraphs": [ "Start with platform selection when choosing tools. Use build guides to formalize strategy rules, backtesting guides to inspect evidence, and deployment guides to validate broker and operational controls." ] }, { "heading": "Treat every backtest as evidence with limits", "paragraphs": [ "Historical results depend on data, timing, costs, fills, parameter choices, and software behavior. Use the linked guides to inspect those assumptions instead of treating one performance number as proof." ] }, { "heading": "Keep broker access and high-risk actions controlled", "paragraphs": [ "Broker support, assets, account permissions, paper or live modes, and authentication methods vary. Connect credentials through BotSpot, keep secrets out of prompts, and review high-risk actions through the required approval flow." ] } ], "cards": [ { "eyebrow": "Automated trading buyer guide", "heading": "Choose the workflow, not just the backtest tool", "summary": "Choose among an AI trading workspace, quantitative platform, broker API, or open-source framework by comparing the complete workflow.", "url": "/guides/automated-trading-platforms" }, { "eyebrow": "Practical AI trading bot guide", "heading": "Build an AI trading bot from testable rules, not a vague prompt", "summary": "Turn a trading idea into explicit rules, inspect AI-generated strategy code, backtest it, test it with paper trading, and prepare it for controlled deployment.", "url": "/guides/how-to-build-an-ai-trading-bot" }, { "eyebrow": "Plain-English algorithmic trading guide", "heading": "Build an algorithmic trading workflow without writing every line yourself", "summary": "Learn how to describe trading rules in plain English, generate inspectable strategy code with AI, backtest it, and validate it without writing every line yourself.", "url": "/guides/algorithmic-trading-without-coding" }, { "eyebrow": "AI strategy backtesting guide", "heading": "Backtest an AI trading strategy without mistaking simulation for proof", "summary": "Build a defensible AI strategy backtest by freezing the hypothesis, checking data timing, documenting execution assumptions, and testing robustness.", "url": "/guides/backtesting-ai-trading-strategies" }, { "eyebrow": "Trading deployment guide", "heading": "Paper trading vs live trading: know what each stage can prove", "summary": "Compare paper and live algorithmic trading, learn what simulations can validate, and use a practical checklist before putting capital at risk.", "url": "/guides/paper-trading-vs-live-trading" }, { "eyebrow": "Backtesting software buyer guide", "heading": "Best backtesting software depends on your strategy workflow", "summary": "Compare backtesting software for AI-assisted, no-code, chart-based, code-first, and MQL5 workflows using documented features and limitations.", "url": "/guides/best-backtesting-software" }, { "eyebrow": "Backtest performance metrics", "heading": "Backtesting metrics explained without magic numbers", "summary": "Learn how CAGR, volatility, Sharpe, Sortino, drawdown, win rate, profit factor, expectancy, and turnover describe a trading backtest.", "url": "/guides/backtesting-metrics-explained" }, { "eyebrow": "Trading strategy validation guide", "heading": "Avoid overfitting a trading strategy before strong backtest results mislead you", "summary": "Reduce backtest overfitting by logging every trial, separating strategy selection from evaluation, preserving unseen data, and testing parameter robustness.", "url": "/guides/avoid-overfitting-trading-strategies" }, { "eyebrow": "Trading strategy validation guide", "heading": "Use walk-forward testing to measure repeated out-of-sample behavior", "summary": "Learn how walk-forward testing uses ordered training and test windows to evaluate trading strategies while reducing leakage and overfitting risk.", "url": "/guides/walk-forward-testing-trading-strategies" }, { "eyebrow": "Backtest data-integrity guide", "heading": "Stop future information from leaking into your backtest", "summary": "Learn how point-in-time data, historical universes, filing timestamps, corporate actions, and indicator alignment prevent false backtest results.", "url": "/guides/look-ahead-bias-and-data-leakage" }, { "eyebrow": "Backtesting execution-cost guide", "heading": "Model slippage, fees, and market impact without making a backtest look safer than it is", "summary": "Learn how to model commissions, bid-ask spreads, slippage, fill timing, liquidity, partial fills, and market impact without inventing universal assumptions.", "url": "/guides/modeling-slippage-fees-and-market-impact" }, { "eyebrow": "Automated trading risk-control guide", "heading": "Build algorithmic trading risk controls around every order and failure state", "summary": "Design algorithmic trading controls for position sizing, exposure, leverage, order limits, drawdowns, monitoring, broker constraints, and emergency stops.", "url": "/guides/algorithmic-trading-risk-management" }, { "eyebrow": "ChatGPT broker connection guide", "heading": "Connect ChatGPT to your broker through BotSpot", "summary": "Connect ChatGPT to BotSpot through OAuth MCP, verify your supported broker and account mode, and keep every trading action behind explicit approval.", "url": "/guides/connect-chatgpt-to-your-broker" }, { "eyebrow": "Claude and broker connection guide", "heading": "Connect Claude to your broker through BotSpot", "summary": "Connect Claude to BotSpot through OAuth, use supported broker context, understand trade approvals, and keep brokerage credentials out of AI prompts.", "url": "/guides/connect-claude-to-your-broker" }, { "eyebrow": "Codex MCP broker guide", "heading": "Connect Codex to your broker through BotSpot", "summary": "Configure BotSpot MCP in Codex, keep broker credentials inside BotSpot, inspect trading context, and stage broker orders behind explicit approval.", "url": "/guides/connect-codex-to-your-broker" } ], "relatedLinks": [ { "label": "Compare AI trading platforms", "url": "/compare" }, { "label": "Explore supported brokers", "url": "/brokers" }, { "label": "MCP for Agents", "url": "/agents" }, { "label": "Review BotSpot case studies", "url": "/case-studies" } ], "sources": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "BotSpot Terms of Service", "url": "/terms" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/compare", "url": "https://botspot.trade/compare", "title": "AI Trading Platform Comparisons | BotSpot", "description": "See how BotSpot combines conversational research, approved direct trading, strategy building, backtesting, and broker connections in one AI trading workspace.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "BotSpot AI trading workspace", "heading": "Trade, research, and automate with one AI agent", "summary": "BotSpot does more than generate trading algorithms. Research an idea, ask for an approved one-time trade, build and backtest a complete strategy, connect a supported broker, and operate the workflow from BotSpot or the AI client you already use.", "primaryAction": { "label": "Start with BotSpot", "url": "/sales?showLogin=1" }, "secondaryAction": { "label": "See MCP setup", "url": "/agents" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "Compare the full job, not one feature", "paragraphs": [ "A code-first quant platform, a broker API, and an AI trading workspace solve different jobs. BotSpot combines a conversational agent with research tools, approved trading actions, strategy code, backtests, supported broker connections, and ongoing operations." ], "bullets": [ "Compare BotSpot with QuantConnect when deciding between an agent-led workspace and a code-first quantitative platform.", "Use BotSpot with a supported broker when you want the broker to hold and execute while BotSpot supplies the AI workflow.", "Review the current broker pages for supported assets, connection modes, authentication methods, and broker-specific warnings." ] } ], "cards": [ { "eyebrow": "Platform comparison", "heading": "BotSpot vs QuantConnect", "summary": "Compare a conversational AI trading workspace with a code-first quantitative research and execution platform.", "url": "/compare/botspot-vs-quantconnect" }, { "eyebrow": "Broker integration", "heading": "Use BotSpot with Alpaca", "summary": "Let Alpaca provide the connected brokerage account while BotSpot supplies research, approved trades, and strategy operations.", "url": "/compare/botspot-vs-alpaca" }, { "eyebrow": "Brokerage platform comparison", "heading": "BotSpot vs Interactive Brokers", "summary": "Compare BotSpot’s AI workflow with Interactive Brokers brokerage accounts, trading platforms, and APIs.", "url": "/compare/botspot-vs-interactive-brokers" }, { "eyebrow": "AI trading agent vs no-code strategy platform", "heading": "BotSpot vs Composer: AI strategy creation and automated trading", "summary": "Compare BotSpot and Composer for AI-assisted strategy creation, research, backtesting, automated execution, and trading workflows.", "url": "/compare/botspot-vs-composer" }, { "eyebrow": "Agent-led workspace vs chart-first trading platform", "heading": "BotSpot vs TrendSpider: AI agent workflow or visual strategy tools", "summary": "Compare BotSpot and TrendSpider for AI-assisted research, strategy creation, backtesting, alerts, broker execution, and automated trading workflows.", "url": "/compare/botspot-vs-trendspider" }, { "eyebrow": "AI trading agent vs code-free rule automation", "heading": "BotSpot vs Capitalise.ai", "summary": "Compare BotSpot and Capitalise.ai for plain-language strategy creation, research, backtesting, simulation, and live automation.", "url": "/compare/botspot-vs-capitalise-ai" }, { "eyebrow": "AI trading agent vs chart-first analysis platform", "heading": "BotSpot vs TradingView: agent-led trading workflow or charts and Pine Script", "summary": "Compare BotSpot and TradingView for conversational research, chart analysis, Pine Script strategies, backtesting, alerts, and broker workflows.", "url": "/compare/botspot-vs-tradingview" }, { "eyebrow": "AI agent vs stock scanner and AI signals", "heading": "BotSpot vs Trade Ideas: build your own trading workflow or follow stock signals", "summary": "Compare BotSpot and Trade Ideas for conversational research, AI trade ideas, stock scanning, backtesting, strategy building, and trading operations.", "url": "/compare/botspot-vs-trade-ideas" }, { "eyebrow": "AI-generated strategies vs no-code trading bots", "heading": "BotSpot vs Option Alpha: build with an AI agent or configure no-code bots", "summary": "Compare BotSpot and Option Alpha for conversational research, no-code bots, strategy backtesting, automation logic, and trading operations.", "url": "/compare/botspot-vs-option-alpha" }, { "eyebrow": "AI strategy workspace vs agentic brokerage", "heading": "BotSpot vs Public.com: strategy workspace or agentic brokerage", "summary": "Compare BotSpot and Public.com for conversational research, AI agents, MCP access, strategy backtesting, brokerage execution, and current connection availability.", "url": "/compare/botspot-vs-public-com" }, { "eyebrow": "Broker connections", "heading": "Explore every supported broker", "summary": "See current BotSpot connection pages for stocks, options, futures, and crypto brokers.", "url": "/brokers" }, { "eyebrow": "Buying guide", "heading": "Choose an automated trading platform", "summary": "Decide whether you need an AI workspace, quantitative platform, broker API, or open-source framework.", "url": "/guides/automated-trading-platforms" } ], "relatedLinks": [ { "label": "MCP for Agents", "url": "/agents" }, { "label": "View supported brokers", "url": "/brokers" }, { "label": "Review BotSpot pricing", "url": "/pricing" } ], "sources": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/compare/botspot-vs-quantconnect", "url": "https://botspot.trade/compare/botspot-vs-quantconnect", "title": "BotSpot vs QuantConnect | AI Trading Platform Comparison", "description": "Compare BotSpot and QuantConnect for conversational research, approved direct trades, algorithm building, backtesting, infrastructure, and broker workflows.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "AI agent vs code-first quant platform", "heading": "BotSpot vs QuantConnect: trade by conversation or build algorithms with AI", "summary": "BotSpot starts with an AI agent that can research, prepare an approved one-time trade when direct trading is enabled, or build and operate a complete algorithm. QuantConnect starts with code and a quantitative research and execution environment.", "primaryAction": { "label": "Start with BotSpot", "url": "/sales?showLogin=1" }, "secondaryAction": { "label": "See MCP setup", "url": "/agents" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "comparisonRows": [ { "capability": "Starting point", "botspot": "Ask in plain English, then inspect the agent work and resulting artifacts.", "alternative": "Write an algorithm against the LEAN engine and QuantConnect platform." }, { "capability": "Direct trading", "botspot": "Request an approved one-time trade through a supported connected broker.", "alternative": "Deploy and run live trading algorithms through the documented platform workflow." }, { "capability": "Research", "botspot": "Use conversational research across market data, public sources, and available account context.", "alternative": "Use datasets, research notebooks, APIs, and code." }, { "capability": "Where you work", "botspot": "Use BotSpot, ChatGPT, Claude, Cursor, Codex, or another compatible MCP client.", "alternative": "Use QuantConnect interfaces, APIs, and the LEAN development model." }, { "capability": "Strategy lifecycle", "botspot": "Build, revise, backtest, connect, and operate a Lumibot strategy in one managed product.", "alternative": "Control algorithm code, research, backtests, optimization, and live deployment in a quantitative platform." } ], "sections": [ { "heading": "What BotSpot can do that changes the comparison", "paragraphs": [ "You do not need to begin by deciding to build an algorithm. Ask the BotSpot agent to research a question, explain what it found, prepare a one-time broker order for your approval, or turn the idea into a testable automated strategy.", "The same BotSpot capabilities can be reached through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients. That makes BotSpot an AI trading workspace, not only a strategy generator." ] }, { "heading": "When QuantConnect may fit better", "bullets": [ "Your quantitative engineering team wants a code-first environment and direct control over the LEAN engine.", "Your workflow is centered on datasets, research notebooks, optimization, and algorithm infrastructure.", "Your team is prepared to own more of the engineering and operational workflow." ] }, { "heading": "Who should use which", "paragraphs": [ "Use BotSpot if you want an AI agent that can research, prepare an approved one-time trade, and generate inspectable Lumibot code without first standing up a quantitative platform.", "Use QuantConnect if your team already writes algorithms against LEAN and wants notebooks, datasets, and infrastructure as the starting point.", "Backtests on both products are historical simulations. They are not live results and do not guarantee future performance. Read drawdown and date range whenever a number is shown." ] }, { "heading": "Risk and limitations", "paragraphs": [ "Neither platform removes market risk. BotSpot requires explicit approval for one-time trade actions, and automated strategies require review before deployment. Backtests are historical simulations and do not guarantee future results." ] } ], "faq": [ { "question": "Can BotSpot trade without first building an algorithm?", "answer": "When direct trading is enabled for the session, BotSpot supports approved one-time trading actions through supported connected brokers. The user reviews and approves the order before submission. Broker, account, asset, and product eligibility still apply." }, { "question": "Can BotSpot also build complete algorithms?", "answer": "Yes. The agent can create and revise Lumibot strategy code, run backtests, and help operate the strategy workflow. Users remain responsible for reviewing logic, assumptions, and risk." } ], "relatedLinks": [ { "label": "MCP for Agents", "url": "/agents" }, { "label": "View supported brokers", "url": "/brokers" }, { "label": "Review BotSpot pricing", "url": "/pricing" } ], "sources": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "QuantConnect algorithm documentation", "url": "https://www.quantconnect.com/docs/v2/writing-algorithms" }, { "label": "LEAN engine repository", "url": "https://github.com/QuantConnect/Lean" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/compare/botspot-vs-composer", "url": "https://botspot.trade/compare/botspot-vs-composer", "title": "BotSpot vs Composer | AI Trading Platform Comparison", "description": "Compare BotSpot and Composer for AI-assisted strategy creation, research, backtesting, automated execution, and trading workflows.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "AI trading agent vs no-code strategy platform", "heading": "BotSpot vs Composer: AI strategy creation and automated trading", "summary": "BotSpot starts with a conversational agent for research, approved one-time trades, and complete Lumibot strategy workflows. Composer centers on Symphonies that users can create with AI, edit visually, backtest, and invest in for automated execution.", "primaryAction": { "label": "Start with BotSpot", "url": "/sales?showLogin=1" }, "secondaryAction": { "label": "See MCP setup", "url": "/agents" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "comparisonRows": [ { "capability": "Starting point", "botspot": "Ask an agent to research a question, prepare an approved trade, or turn an idea into a strategy.", "alternative": "Describe a strategy to Composer’s AI-assisted editor or build a Symphony from visual blocks." }, { "capability": "Strategy artifact", "botspot": "Create and revise inspectable Lumibot strategy code.", "alternative": "Build a Symphony from assets, weights, conditions, filters, and groups in a no-code visual editor." }, { "capability": "Backtesting", "botspot": "Run historical simulations as part of the generated strategy workflow.", "alternative": "Backtest Symphonies and inspect hypothetical metrics, allocations, and comparisons." }, { "capability": "Trading workflow", "botspot": "Use supported connected brokers for approved one-time actions or deployed automated strategies.", "alternative": "Invest in a Symphony and let Composer trade toward its target allocations." } ], "sections": [ { "heading": "Same broad promise, different product boundary", "paragraphs": [ "Both products support natural-language strategy creation and historical backtesting. BotSpot wraps those capabilities inside a broader trading agent that can research, prepare approved one-time trades, generate Lumibot code, and operate through supported broker connections.", "Composer presents strategies as Symphonies. Its documented workflow combines AI creation, a visual block editor, backtests, discovery, and automated execution inside Composer." ] }, { "heading": "When Composer may fit better", "bullets": [ "You prefer a no-code visual strategy made from documented Symphony building blocks.", "You want to browse, inspect, edit, or invest in pre-built and community Symphonies.", "You want strategy creation, backtesting, and automated allocation execution inside Composer’s brokerage workflow." ] }, { "heading": "Backtests do not equal live results", "paragraphs": [ "Composer documents its backtests as hypothetical simulations and explains that historical inputs and execution assumptions differ from live trading. BotSpot backtests are historical simulations too. Neither product can guarantee future results." ] }, { "heading": "Who should use which", "paragraphs": [ "Use BotSpot when you want a conversational agent that can research, prepare an approved one-time trade, and build inspectable Lumibot strategies through currently supported brokers.", "Use the other product on this page when its documented workflow is the job you need first: specialist charting, brokerage, no-code allocation, or research tooling rather than the full BotSpot workspace.", "Backtests mentioned for either product are historical simulations. They are not live results and do not guarantee future performance. Include drawdown and date range whenever a number is shown." ] } ], "faq": [ { "question": "Can both BotSpot and Composer create strategies from natural language?", "answer": "Yes. BotSpot can turn a conversation into inspectable Lumibot strategy code. Composer documents an AI-assisted editor that converts a strategy description into a Symphony that can be inserted and backtested." }, { "question": "Does BotSpot require every request to become an algorithm?", "answer": "No. BotSpot can research conversationally and, when direct trading is enabled, prepare a supported one-time order for explicit user approval." }, { "question": "Do Composer or BotSpot backtests predict future returns?", "answer": "No. Backtests model historical scenarios using assumptions. Market conditions, data, fees, slippage, order eligibility, and live execution can produce different results." } ], "relatedLinks": [ { "label": "Compare AI trading platforms", "url": "/compare" }, { "label": "Choose an automated trading platform", "url": "/guides/automated-trading-platforms" }, { "label": "MCP for Agents", "url": "/agents" }, { "label": "View supported brokers", "url": "/brokers" } ], "sources": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "Composer product overview", "url": "https://www.composer.trade/" }, { "label": "Composer Create with AI documentation", "url": "https://help.composer.trade/article/108-create-with-ai" }, { "label": "Composer backtest basics", "url": "https://help.composer.trade/article/67-backtest-basics" }, { "label": "Composer automated trading documentation", "url": "https://help.composer.trade/article/65-how-does-composer-trade" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/compare/botspot-vs-trendspider", "url": "https://botspot.trade/compare/botspot-vs-trendspider", "title": "BotSpot vs TrendSpider | AI Trading Platform Comparison", "description": "Compare BotSpot and TrendSpider for AI-assisted research, strategy creation, backtesting, alerts, broker execution, and automated trading workflows.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "Agent-led workspace vs chart-first trading platform", "heading": "BotSpot vs TrendSpider: AI agent workflow or visual strategy tools", "summary": "BotSpot starts with an AI agent that can research, prepare an approved one-time trade, or build and operate a Lumibot strategy. TrendSpider starts with charts, market-analysis tools, no-code strategy testing, alerts, bots, and its Sidekick AI analyst.", "primaryAction": { "label": "Start with BotSpot", "url": "/sales?showLogin=1" }, "secondaryAction": { "label": "See MCP setup", "url": "/agents" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "comparisonRows": [ { "capability": "Starting point", "botspot": "Ask an agent to investigate an idea, prepare an approved action, or turn the idea into a strategy.", "alternative": "Begin with charts, screeners, conditions, Strategy Tester, or Sidekick analysis inside TrendSpider." }, { "capability": "Strategy creation", "botspot": "Create and revise inspectable Lumibot strategy code through an agent-led workflow.", "alternative": "Define rules with natural language or point-and-click menus, with JavaScript available for custom indicators." }, { "capability": "Backtesting", "botspot": "Ask the agent to run and revise Lumibot backtests as part of the managed strategy lifecycle.", "alternative": "Use the no-code Strategy Tester to inspect trade results, risk statistics, and strategy behavior." }, { "capability": "Actions and automation", "botspot": "Review and approve a supported one-time broker order, or connect and operate an automated Lumibot strategy.", "alternative": "Deploy strategy logic through cloud alerts and bots, supported broker integrations, or webhooks." } ], "sections": [ { "heading": "Different operating models", "paragraphs": [ "TrendSpider concentrates chart analysis, condition building, no-code backtesting, alerts, bots, and Sidekick inside its trading platform. BotSpot concentrates the workflow around an agent that can move from research to an approved one-time action or an inspectable Lumibot strategy.", "BotSpot capabilities can also be reached through compatible MCP clients such as ChatGPT, Claude, Cursor, and Codex." ] }, { "heading": "When TrendSpider may fit better", "bullets": [ "Charts, technical conditions, scanners, and visual market analysis are the center of your workflow.", "You prefer point-and-click strategy rules and no-code backtesting over generated strategy code.", "You want Sidekick analysis, Strategy Tester, and cloud alerts or bots inside one chart-first platform." ] }, { "heading": "Risk and limitations", "paragraphs": [ "Neither product removes market risk. Backtests are historical simulations, configuration choices can materially change results, and past results do not guarantee future performance." ] }, { "heading": "Who should use which", "paragraphs": [ "Use BotSpot when you want a conversational agent that can research, prepare an approved one-time trade, and build inspectable Lumibot strategies through currently supported brokers.", "Use the other product on this page when its documented workflow is the job you need first: specialist charting, brokerage, no-code allocation, or research tooling rather than the full BotSpot workspace.", "Backtests mentioned for either product are historical simulations. They are not live results and do not guarantee future performance. Include drawdown and date range whenever a number is shown." ] } ], "faq": [ { "question": "Does TrendSpider have an AI assistant?", "answer": "Yes. TrendSpider describes Sidekick as an AI market analyst that can answer questions, analyze charts, review backtest results, and surface insights." }, { "question": "Can BotSpot and TrendSpider both backtest strategies?", "answer": "Yes, through different workflows. BotSpot backtests Lumibot strategies through its agent-led lifecycle. TrendSpider provides a no-code Strategy Tester." }, { "question": "Can BotSpot place a trade without first building a strategy?", "answer": "When direct trading is enabled, BotSpot can prepare a supported one-time broker order for user review and approval." } ], "relatedLinks": [ { "label": "Compare AI trading platforms", "url": "/compare" }, { "label": "Choose an automated trading platform", "url": "/guides/automated-trading-platforms" }, { "label": "MCP for Agents", "url": "/agents" }, { "label": "View supported brokers", "url": "/brokers" } ], "sources": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "TrendSpider product overview", "url": "https://trendspider.com/product/" }, { "label": "TrendSpider strategy development and backtesting", "url": "https://trendspider.com/product/strategy-development-and-backtesting-tools/" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/compare/botspot-vs-capitalise-ai", "url": "https://botspot.trade/compare/botspot-vs-capitalise-ai", "title": "BotSpot vs Capitalise.ai | AI Trading Platform Comparison", "description": "Compare BotSpot and Capitalise.ai for plain-language strategy creation, research, backtesting, simulation, and live automation.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "AI trading agent vs code-free rule automation", "heading": "BotSpot vs Capitalise.ai", "summary": "BotSpot combines conversational research, approved one-time trades, and inspectable Lumibot strategy workflows. Capitalise.ai focuses on creating entry and exit rules in everyday language, then backtesting, simulating, or running those rules live.", "primaryAction": { "label": "Start with BotSpot", "url": "/sales?showLogin=1" }, "secondaryAction": { "label": "See MCP setup", "url": "/agents" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "comparisonRows": [ { "capability": "Starting point", "botspot": "Ask an agent to research, prepare an approved trade, or build a complete strategy.", "alternative": "Write entry and exit rules in plain language through Capitalise.ai’s Strategy Creation Wizard." }, { "capability": "Strategy representation", "botspot": "Generate and revise inspectable Lumibot strategy code.", "alternative": "Review parsed conditions, rules, and actions without writing code." }, { "capability": "Testing modes", "botspot": "Backtest generated strategies and review logic and assumptions before deployment.", "alternative": "Choose among documented Backtest, Simulate, and Run Live modes." }, { "capability": "Trading workflow", "botspot": "Use supported connected brokers for approved one-time actions or automated strategy operation.", "alternative": "Run confirmed rule-based strategies through Capitalise.ai’s supported broker and integration workflow." } ], "sections": [ { "heading": "Different meanings of conversational trading", "paragraphs": [ "Capitalise.ai uses everyday language to define explicit entry and exit conditions. Its confirmation flow exposes parsed rules, actions, execution mode, limits, and strategy settings before a strategy runs.", "BotSpot begins with a broader agent conversation. Users can investigate an idea, request an approved one-time action, or create and operate an inspectable Lumibot strategy." ] }, { "heading": "When Capitalise.ai may fit better", "bullets": [ "You want code-free rules centered on entry conditions, exit conditions, and execution modes.", "You prefer a structured wizard that confirms parsed rules and actions before running.", "You want documented backtest, live simulation, and live strategy modes inside one rule-automation workflow." ] }, { "heading": "Simulation and live execution can diverge", "paragraphs": [ "Capitalise.ai documents differences among backtests, simulations, and live trading, including execution, partial fills, slippage, price sources, and fees. Neither simulated mode guarantees live results." ] }, { "heading": "Who should use which", "paragraphs": [ "Use BotSpot when you want a conversational agent that can research, prepare an approved one-time trade, and build inspectable Lumibot strategies through currently supported brokers.", "Use the other product on this page when its documented workflow is the job you need first: specialist charting, brokerage, no-code allocation, or research tooling rather than the full BotSpot workspace.", "Backtests mentioned for either product are historical simulations. They are not live results and do not guarantee future performance. Include drawdown and date range whenever a number is shown." ] } ], "faq": [ { "question": "Does Capitalise.ai require coding?", "answer": "No. Capitalise.ai documents a code-free workflow where users define entry and exit strategies in everyday language and review the interpreted rules before running them." }, { "question": "What does BotSpot add beyond plain-language strategy rules?", "answer": "BotSpot can research conversationally, prepare supported one-time trades for explicit approval, and create, revise, backtest, connect, and operate inspectable Lumibot strategies." }, { "question": "Should backtest, simulation, and live results match?", "answer": "Not necessarily. Execution, fills, slippage, data, price methodology, and fees can produce different outcomes." } ], "relatedLinks": [ { "label": "Compare AI trading platforms", "url": "/compare" }, { "label": "Choose an automated trading platform", "url": "/guides/automated-trading-platforms" }, { "label": "MCP for Agents", "url": "/agents" }, { "label": "View supported brokers", "url": "/brokers" } ], "sources": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "Capitalise.ai product overview", "url": "https://support.capitalise.ai/en/articles/2164262-about-capitalise-ai" }, { "label": "Capitalise.ai strategy confirmation", "url": "https://support.capitalise.ai/en/articles/5982066-confirming-the-strategy" }, { "label": "Capitalise.ai mode differences", "url": "https://support.capitalise.ai/en/articles/6148015-differences-between-modes" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/compare/botspot-vs-tradingview", "url": "https://botspot.trade/compare/botspot-vs-tradingview", "title": "BotSpot vs TradingView | AI Trading Platform Comparison", "description": "Compare BotSpot and TradingView for conversational research, chart analysis, Pine Script strategies, backtesting, alerts, and broker workflows.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "AI trading agent vs chart-first analysis platform", "heading": "BotSpot vs TradingView: agent-led trading workflow or charts and Pine Script", "summary": "BotSpot starts with an AI agent that can research, prepare an approved one-time trade, or build and operate a Lumibot strategy. TradingView starts with Supercharts, indicators, screeners, Pine Script strategies, alerts, and broker-connected chart trading.", "primaryAction": { "label": "Start with BotSpot", "url": "/sales?showLogin=1" }, "secondaryAction": { "label": "See MCP setup", "url": "/agents" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "comparisonRows": [ { "capability": "Starting point", "botspot": "Ask in plain English, inspect the agent work, and decide whether to research further, trade, or automate.", "alternative": "Open Supercharts to analyze symbols with charts, indicators, drawings, screeners, news, and alerts." }, { "capability": "Strategy authoring", "botspot": "Ask the agent to create and revise inspectable Lumibot strategy code.", "alternative": "Write a Pine Script strategy or use a built-in or published community strategy." }, { "capability": "Backtesting", "botspot": "Run and revise Lumibot backtests within the same agent-led strategy workflow.", "alternative": "Use Pine strategies to simulate hypothetical orders and inspect Strategy Tester reports." }, { "capability": "Broker actions", "botspot": "Request a supported one-time broker order, inspect it, and approve it before submission.", "alternative": "Connect a supported broker and trade from Supercharts; Pine strategies cannot directly place exchange orders." } ], "sections": [ { "heading": "Different centers of gravity", "paragraphs": [ "TradingView centers the workflow on charts. Pine strategies simulate trades through a broker emulator, produce strategy reports, and can generate realtime alerts. TradingView also supports manual order entry through connected brokers.", "BotSpot centers the workflow on an AI agent that can move from research to an approved one-time action or an inspectable Lumibot strategy." ] }, { "heading": "When TradingView may fit better", "bullets": [ "Advanced interactive charts, indicators, drawings, screeners, and visual market monitoring are your main tools.", "You already author or use Pine Script indicators and strategies.", "You want chart-based manual trading through a TradingView-supported broker." ] }, { "heading": "Execution and backtest limits matter", "paragraphs": [ "TradingView distinguishes chart trading from Pine strategy simulation. Pine scripts cannot directly place exchange orders; external tooling can act on webhook alerts. Backtests on either platform remain simulations and cannot guarantee future performance." ] }, { "heading": "Who should use which", "paragraphs": [ "Use BotSpot when you want a conversational agent that can research, prepare an approved one-time trade, and build inspectable Lumibot strategies through currently supported brokers.", "Use the other product on this page when its documented workflow is the job you need first: specialist charting, brokerage, no-code allocation, or research tooling rather than the full BotSpot workspace.", "Backtests mentioned for either product are historical simulations. They are not live results and do not guarantee future performance. Include drawdown and date range whenever a number is shown." ] } ], "faq": [ { "question": "Is BotSpot a replacement for TradingView charts?", "answer": "Not directly. TradingView centers on charts, indicators, screeners, Pine Script, and alerts. BotSpot centers on conversational research, approved trading actions, and the Lumibot strategy lifecycle." }, { "question": "Can a TradingView Pine strategy place live broker orders?", "answer": "TradingView’s Pine documentation says strategies and indicators cannot directly place exchange orders. They can emit alerts for external execution tools." }, { "question": "Can BotSpot backtest automated strategies?", "answer": "Yes. BotSpot can create, revise, and backtest Lumibot strategies. Users remain responsible for reviewing code, assumptions, simulated results, and deployment risk." } ], "relatedLinks": [ { "label": "Compare AI trading platforms", "url": "/compare" }, { "label": "Choose an automated trading platform", "url": "/guides/automated-trading-platforms" }, { "label": "MCP for Agents", "url": "/agents" }, { "label": "View supported brokers", "url": "/brokers" } ], "sources": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "TradingView Supercharts guide", "url": "https://www.tradingview.com/support/solutions/43000746464-getting-started-with-supercharts/" }, { "label": "TradingView Pine strategies", "url": "https://www.tradingview.com/pine-script-docs/concepts/strategies/" }, { "label": "TradingView strategy FAQ", "url": "https://www.tradingview.com/pine-script-docs/faq/strategies/" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/compare/botspot-vs-trade-ideas", "url": "https://botspot.trade/compare/botspot-vs-trade-ideas", "title": "BotSpot vs Trade Ideas | AI Trading Platform Comparison", "description": "Compare BotSpot and Trade Ideas for conversational research, AI trade ideas, stock scanning, backtesting, strategy building, and trading operations.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "AI agent vs stock scanner and AI signals", "heading": "BotSpot vs Trade Ideas: build your own trading workflow or follow stock signals", "summary": "BotSpot starts with a conversational agent that can research a question, prepare an approved one-time trade, or build and operate a Lumibot strategy. Trade Ideas centers on real-time stock scanning, configurable alerts, Holly AI trade suggestions, and scanner-based trading workflows.", "primaryAction": { "label": "Start with BotSpot", "url": "/sales?showLogin=1" }, "secondaryAction": { "label": "See MCP setup", "url": "/agents" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "comparisonRows": [ { "capability": "Starting point", "botspot": "Ask a market or strategy question in plain English, then inspect the agent work and artifacts.", "alternative": "Configure stock scans and alerts or review strategies and trades selected by Holly AI." }, { "capability": "AI role", "botspot": "Research an idea, prepare an approved direct trade, or turn the idea into a custom Lumibot strategy.", "alternative": "Holly presents real-time stock trade suggestions with entries, stops, and targets." }, { "capability": "Strategy building and testing", "botspot": "Generate and revise inspectable strategy code, then run Lumibot backtests.", "alternative": "Define strategies with alerts, filters, and formulas, then evaluate them with OddsMaker." }, { "capability": "Trading operations", "botspot": "Connect a supported broker, review one-time orders, and operate automated strategies.", "alternative": "Use Brokerage Plus for one-click orders, simulation, participating brokers, and configured automation." } ], "sections": [ { "heading": "Signal discovery and agent-led strategy development solve different jobs", "paragraphs": [ "Trade Ideas is built around finding and ranking stock events with configurable scanners, charts, Holly AI suggestions, OddsMaker backtests, and Brokerage Plus trading tools.", "BotSpot begins with an open-ended agent interaction that can move from research to an approved one-time order or to generated, inspectable strategy code and operations." ] }, { "heading": "When Trade Ideas may fit better", "bullets": [ "Your main job is monitoring real-time stock scanners, alerts, rankings, and charts.", "You want Holly AI to surface prepared stock trade suggestions with entries, stops, and targets.", "Your workflow already uses Trade Ideas alerts, filters, custom formulas, and Brokerage Plus." ] }, { "heading": "Risk and limitations", "paragraphs": [ "Neither platform removes trading risk. Trade Ideas documents OddsMaker differences from live execution and recommends backtesting followed by paper testing before live trading." ] }, { "heading": "Who should use which", "paragraphs": [ "Use BotSpot when you want a conversational agent that can research, prepare an approved one-time trade, and build inspectable Lumibot strategies through currently supported brokers.", "Use the other product on this page when its documented workflow is the job you need first: specialist charting, brokerage, no-code allocation, or research tooling rather than the full BotSpot workspace.", "Backtests mentioned for either product are historical simulations. They are not live results and do not guarantee future performance. Include drawdown and date range whenever a number is shown." ] } ], "faq": [ { "question": "Is Trade Ideas Holly the same kind of AI agent as BotSpot?", "answer": "Trade Ideas describes Holly as a virtual assistant that selects strategies and presents real-time stock trade suggestions. BotSpot spans conversational research, approved direct trading, and custom Lumibot strategy operations." }, { "question": "Can Trade Ideas automate trading strategies?", "answer": "Yes. Trade Ideas documents Brokerage Plus automation for strategies based on scans and custom formulas, with simulator testing recommended before live use." }, { "question": "Which platform fits a stock-scanner workflow?", "answer": "Trade Ideas directly centers on real-time stock scans, alerts, ranked lists, charts, and Holly suggestions. BotSpot fits a broader agent-led strategy workflow." } ], "relatedLinks": [ { "label": "Compare AI trading platforms", "url": "/compare" }, { "label": "Choose an automated trading platform", "url": "/guides/automated-trading-platforms" }, { "label": "MCP for Agents", "url": "/agents" }, { "label": "View supported brokers", "url": "/brokers" } ], "sources": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "Trade Ideas feature guide", "url": "https://www.trade-ideas.com/guide/chapter/8_2/8.2New_Tab.html" }, { "label": "Trade Ideas Holly AI guide", "url": "https://www.trade-ideas.com/hollyguide/" }, { "label": "Trade Ideas Brokerage Plus guide", "url": "https://www.trade-ideas.com/guide/chapter/21/21Brokerage_Plus.html" }, { "label": "Trade Ideas OddsMaker guide", "url": "https://forums.trade-ideas.com/guide/chapter/22/22Backtesting_Oddsmaker.html" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/compare/botspot-vs-option-alpha", "url": "https://botspot.trade/compare/botspot-vs-option-alpha", "title": "BotSpot vs Option Alpha | AI Trading Bot Comparison", "description": "Compare BotSpot and Option Alpha for conversational research, no-code bots, strategy backtesting, automation logic, and trading operations.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "AI-generated strategies vs no-code trading bots", "heading": "BotSpot vs Option Alpha: build with an AI agent or configure no-code bots", "summary": "BotSpot uses a conversational agent to research, prepare approved one-time trades, and create or operate inspectable Lumibot strategies. Option Alpha provides no-code stock and options bots built from templates, recipes, decisions, actions, scanners, and monitors.", "primaryAction": { "label": "Start with BotSpot", "url": "/sales?showLogin=1" }, "secondaryAction": { "label": "See MCP setup", "url": "/agents" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "comparisonRows": [ { "capability": "Starting point", "botspot": "Describe a research question, trade request, or strategy in plain English.", "alternative": "Customize a bot template or create a bot from recipes and predefined automation components." }, { "capability": "Strategy representation", "botspot": "Create and revise inspectable Lumibot strategy code through conversation.", "alternative": "Build no-code logic from actions, decisions, loops, scanner automations, and monitor automations." }, { "capability": "Backtesting", "botspot": "Run backtests on generated Lumibot strategies, then revise code and assumptions.", "alternative": "Backtest documented 0DTE and next-day options strategies and generate a bot from a selected test." }, { "capability": "Automation and controls", "botspot": "Operate connected strategies and review supported one-time trade requests before submission.", "alternative": "Schedule scanners and monitors while bot-level allocation and position controls govern new positions." } ], "sections": [ { "heading": "Generated code and visual recipes provide different kinds of control", "paragraphs": [ "Option Alpha packages strategy logic as reusable no-code recipes and decision trees. Its scanners look for entries, monitors manage positions, and bot-level controls constrain allocation and position counts.", "BotSpot lets users begin with a broader conversation, inspect generated Lumibot code, request revisions, run backtests, connect a supported broker, and operate the strategy." ] }, { "heading": "When Option Alpha may fit better", "bullets": [ "You want a no-code bot builder based on templates, recipes, decisions, and visual automation paths.", "Your workflow centers on stock or options bots, especially documented 0DTE and next-day options testing.", "You prefer predefined scanner and monitor components with bot-level allocation and position controls." ] }, { "heading": "Risk and limitations", "paragraphs": [ "No automation or backtest guarantees future results. Option Alpha recommends testing automations and paper trading before using live capital. BotSpot users must inspect generated logic and validate assumptions before deployment." ] }, { "heading": "Who should use which", "paragraphs": [ "Use BotSpot when you want a conversational agent that can research, prepare an approved one-time trade, and build inspectable Lumibot strategies through currently supported brokers.", "Use the other product on this page when its documented workflow is the job you need first: specialist charting, brokerage, no-code allocation, or research tooling rather than the full BotSpot workspace.", "Backtests mentioned for either product are historical simulations. They are not live results and do not guarantee future performance. Include drawdown and date range whenever a number is shown." ] } ], "faq": [ { "question": "Does Option Alpha require coding?", "answer": "No. Option Alpha documents automated stock and options strategies built without code from templates, recipes, actions, decisions, scanners, and monitors." }, { "question": "Can BotSpot automate options strategies?", "answer": "BotSpot can build and operate Lumibot strategies, but options availability depends on strategy support, connected broker, account permissions, and product eligibility." }, { "question": "Which platform fits users who want to inspect strategy code?", "answer": "BotSpot generates inspectable Lumibot strategy code. Option Alpha fits users who prefer no-code recipes and visual automation logic." } ], "relatedLinks": [ { "label": "Compare AI trading platforms", "url": "/compare" }, { "label": "Choose an automated trading platform", "url": "/guides/automated-trading-platforms" }, { "label": "MCP for Agents", "url": "/agents" }, { "label": "View supported brokers", "url": "/brokers" } ], "sources": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "Option Alpha bots documentation", "url": "https://docs.optionalpha.com/tools/bots" }, { "label": "Option Alpha automations documentation", "url": "https://docs.optionalpha.com/tools/bots/automations" }, { "label": "Option Alpha backtesting documentation", "url": "https://docs.optionalpha.com/tools/backtesting" }, { "label": "Option Alpha testing guidance", "url": "https://docs.optionalpha.com/technical-documentation/troubleshooting/testing-automations" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/compare/botspot-vs-public-com", "url": "https://botspot.trade/compare/botspot-vs-public-com", "title": "BotSpot vs Public.com | AI Trading Platform Comparison", "description": "Compare BotSpot and Public.com for conversational research, AI agents, MCP access, strategy backtesting, brokerage execution, and current connection availability.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "AI strategy workspace vs agentic brokerage", "heading": "BotSpot vs Public.com: strategy workspace or agentic brokerage", "summary": "Both BotSpot and Public support conversational market workflows, automated trading, and MCP access. BotSpot focuses on building, revising, backtesting, and operating inspectable Lumibot strategies across supported broker connections. Public combines brokerage accounts, native AI Agents, market data, and execution. The current BotSpot broker manifest does not list Public as a supported connection.", "primaryAction": { "label": "Start with BotSpot", "url": "/sales?showLogin=1" }, "secondaryAction": { "label": "View supported BotSpot brokers", "url": "/brokers" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "comparisonRows": [ { "capability": "Product role", "botspot": "AI trading workspace for research, approved one-time trades, and Lumibot strategy workflows using supported connected brokers.", "alternative": "Brokerage and multi-asset investing platform with AI Agents, research tools, APIs, and native execution." }, { "capability": "Building automation", "botspot": "Create, inspect, revise, and operate strategy code through a conversational agent.", "alternative": "Describe conditions and actions in plain English, review the proposed Agent workflow, then activate it inside a Public account." }, { "capability": "Backtesting", "botspot": "Backtest inspectable Lumibot strategy code before deciding whether to deploy it.", "alternative": "Public’s Agent help documentation lists Agent backtesting as not yet available; Generated Assets has a separate historical custom-index backtest." }, { "capability": "AI and MCP access", "botspot": "Use BotSpot or compatible MCP clients including ChatGPT, Claude, Cursor, and Codex.", "alternative": "Use built-in Public Agents or connect a Public brokerage account to documented third-party AI clients through Public’s MCP server." }, { "capability": "Authorization model", "botspot": "Review and approve a supported one-time trade before submission; review strategy logic before deployment.", "alternative": "Review and activate an Agent workflow first; active Agents can then execute approved instructions without confirmation for every transaction." } ], "sections": [ { "heading": "Where BotSpot and Public overlap and diverge", "paragraphs": [ "Both products support plain-English research and trading workflows, automation, and MCP access. BotSpot supplies a strategy-building and operations layer around supported connected brokers. Public supplies brokerage accounts plus native Agents, market data, account actions, APIs, and execution.", "BotSpot’s clearest distinction is inspectable Lumibot code, revisions, strategy backtests, and a supported multi-broker workflow." ] }, { "heading": "When Public may fit better", "bullets": [ "You want brokerage, market data, cash movement, and agent execution inside one Public account.", "You want native conditional workflows across supported stocks, options, and crypto.", "You want Public-specific investing products or direct MCP access to a Public brokerage account." ] }, { "heading": "Connection status, availability, and risk", "paragraphs": [ "The current BotSpot public broker manifest does not list Public as a supported connection. This page compares separate products and does not imply an integration.", "Public’s help center currently describes built-in Agent workflows as web-only and rolling out through a waitlist. Automated trading can lose money, and historical results do not guarantee future performance." ] }, { "heading": "Who should use which", "paragraphs": [ "Use BotSpot when you want a conversational agent that can research, prepare an approved one-time trade, and build inspectable Lumibot strategies through currently supported brokers.", "Use the other product on this page when its documented workflow is the job you need first: specialist charting, brokerage, no-code allocation, or research tooling rather than the full BotSpot workspace.", "Backtests mentioned for either product are historical simulations. They are not live results and do not guarantee future performance. Include drawdown and date range whenever a number is shown." ] } ], "faq": [ { "question": "Can BotSpot connect directly to Public.com?", "answer": "Not through the current standard broker list. Public is not listed in BotSpot’s public broker connection manifest as of August 14, 2026." }, { "question": "Do BotSpot and Public.com both support MCP?", "answer": "Yes, but they provide separate MCP products. BotSpot exposes its workflow to compatible AI clients. Public’s MCP server connects a Public brokerage account to documented third-party AI clients." }, { "question": "Can Public Agents backtest a trading strategy?", "answer": "Public’s current Agent help documentation lists backtesting as not yet available for Agents. BotSpot can generate and backtest inspectable Lumibot strategy code." } ], "relatedLinks": [ { "label": "Compare AI trading platforms", "url": "/compare" }, { "label": "Choose an automated trading platform", "url": "/guides/automated-trading-platforms" }, { "label": "MCP for Agents", "url": "/agents" }, { "label": "View supported brokers", "url": "/brokers" } ], "sources": [ { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "Public AI Agents", "url": "https://public.com/ai-agents" }, { "label": "Public Agents basics", "url": "https://help.public.com/en/articles/15435640-agents-the-basics" }, { "label": "Public Agent controls", "url": "https://help.public.com/en/articles/15435700-agents-setting-up-and-controlling-agents" }, { "label": "Public MCP server", "url": "https://public.com/mcp-trading" }, { "label": "Public Agentic Brokerage disclosures", "url": "https://public.com/disclosures/agenticterms" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/compare/botspot-vs-alpaca", "url": "https://botspot.trade/compare/botspot-vs-alpaca", "title": "Use BotSpot with Alpaca | AI Trading and Broker Integration", "description": "Connect Alpaca to BotSpot for conversational research, approved one-time trades, AI strategy building, backtesting, and automated operations.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "AI workspace plus connected broker", "heading": "Use BotSpot with Alpaca", "summary": "BotSpot supplies the AI trading workspace. Alpaca supplies the connected brokerage account and execution layer. Together, you can research, request an approved one-time trade when direct trading is enabled, or build and operate a complete automated strategy.", "primaryAction": { "label": "Connect Alpaca to BotSpot", "url": "/account-settings/broker-connections?action=add&broker=alpaca" }, "secondaryAction": { "label": "Explore all broker connections", "url": "/brokers" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "comparisonRows": [ { "capability": "AI workspace", "botspot": "Conversational research, trading actions, and strategy lifecycle.", "alternative": "Alpaca provides brokerage and developer APIs." }, { "capability": "Account and execution", "botspot": "Uses your supported connected broker account.", "alternative": "Alpaca holds the brokerage account and executes eligible orders." }, { "capability": "Application ownership", "botspot": "Provides the product, agent, revisions, backtests, approvals, and operations workflow.", "alternative": "Direct API users build and maintain their own application layer." } ], "sections": [ { "heading": "Why this is an integration, not a winner-take-all comparison", "paragraphs": [ "Alpaca and BotSpot solve different parts of the workflow. Connect Alpaca when you want its brokerage account and API execution with BotSpot handling the conversational product layer around research, approved trades, and automation." ], "bullets": [ "Ask the agent to research an idea before deciding whether to trade or automate it.", "Prepare a one-time order, inspect the details, and approve it before BotSpot submits it.", "Build, revise, backtest, and operate a Lumibot algorithm using the same connected account workflow." ] }, { "heading": "Who should use which", "paragraphs": [ "Use BotSpot with Alpaca when you want the AI workspace for research, approved one-time trades, and Lumibot strategy operations while Alpaca holds the account.", "Use Alpaca APIs directly when you want to build your own application without BotSpot.", "These products stack rather than replace each other. Simulated BotSpot backtests are not Alpaca live results. Include drawdown and date range whenever a number is shown." ] }, { "heading": "Connection details", "paragraphs": [ "BotSpot currently lists Alpaca for stocks, options, and crypto with paper and live connection modes. OAuth and API-key connection methods are available. Actual products, permissions, data, fees, and order eligibility depend on the Alpaca account and current broker policies." ] } ], "faq": [ { "question": "Can BotSpot connect to Alpaca?", "answer": "Yes. Alpaca is listed in BotSpot as a supported connection for paper and live workflows. Available products and permissions depend on your Alpaca account." }, { "question": "Do I need to build an algorithm to trade through BotSpot and Alpaca?", "answer": "No. When direct trading is enabled, BotSpot can prepare an approved one-time trade for a supported connected account. You can also use the agent to build and backtest a complete automated strategy." } ], "relatedLinks": [ { "label": "View the Alpaca broker page", "url": "/brokers/alpaca" }, { "label": "MCP for Agents", "url": "/agents" }, { "label": "View every supported broker", "url": "/brokers" } ], "sources": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "Alpaca documentation", "url": "https://docs.alpaca.markets/us/docs/trading-api" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/compare/botspot-vs-interactive-brokers", "url": "https://botspot.trade/compare/botspot-vs-interactive-brokers", "title": "BotSpot vs Interactive Brokers | Trading Platform Comparison", "description": "Compare BotSpot and Interactive Brokers by AI workflow, brokerage access, APIs, automation, and current connection availability.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "AI workspace vs brokerage platform", "heading": "BotSpot vs Interactive Brokers", "summary": "BotSpot supplies a conversational research, trading, and strategy workflow. Interactive Brokers supplies brokerage accounts, trading platforms, and APIs. The current BotSpot broker source does not list Interactive Brokers as an available connection.", "primaryAction": { "label": "View supported BotSpot brokers", "url": "/brokers" }, "secondaryAction": { "label": "See MCP setup", "url": "/agents" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "comparisonRows": [ { "capability": "Starting point", "botspot": "Ask an agent to research, prepare an approved trade, or build inspectable strategy code.", "alternative": "Open an Interactive Brokers account and use TWS, Client Portal, or IBKR APIs." }, { "capability": "Custody and execution", "botspot": "Uses a supported connected broker. BotSpot does not hold customer funds.", "alternative": "Interactive Brokers holds the brokerage account and executes eligible orders." }, { "capability": "Strategy automation", "botspot": "Build, backtest, and operate Lumibot strategies in a managed workspace.", "alternative": "Build custom applications against IBKR APIs or use IBKR desktop and web platforms." }, { "capability": "Current BotSpot connection", "botspot": "Not listed as an available standard connection in the public BotSpot broker manifest.", "alternative": "Direct brokerage access does not require BotSpot." } ], "sections": [ { "heading": "The practical difference", "paragraphs": [ "BotSpot focuses on the work around a trade or strategy: research, user-approved actions, code, simulated backtests, revisions, and operations. Interactive Brokers focuses on the brokerage account, execution, trading interfaces, and developer APIs.", "A simulated BotSpot backtest is not an IBKR live track record. If you compare numbers, include drawdown and the simulation date range, and treat the result as hypothetical." ] }, { "heading": "Connection status matters", "paragraphs": [ "The current BotSpot public broker manifest does not list Interactive Brokers as an available standard connection. This page compares product roles and does not imply an integration. Check the broker list before assuming a BotSpot bot can place IBKR orders." ] }, { "heading": "Who should use which", "paragraphs": [ "Use BotSpot if you want an AI workspace for research, approved one-time trades, and automated Lumibot strategies through a currently supported broker.", "Use Interactive Brokers if you need IBKR account features, TWS or Client Portal, or you are building directly on IBKR APIs.", "Use both only if you later connect through a supported path. Today this comparison does not claim that BotSpot can drive an IBKR account." ] } ], "faq": [ { "question": "Is Interactive Brokers currently listed as a BotSpot broker connection?", "answer": "No. The current BotSpot public broker manifest does not list Interactive Brokers as an available standard connection. Check the manifest for the current supported set." } ], "relatedLinks": [ { "label": "View supported BotSpot brokers", "url": "/brokers" }, { "label": "MCP for Agents", "url": "/agents" } ], "sources": [ { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "Interactive Brokers API overview", "url": "https://www.interactivebrokers.com/campus/ibkr-api-page/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides/automated-trading-platforms", "url": "https://botspot.trade/guides/automated-trading-platforms", "title": "How to Choose an Automated Trading Platform | BotSpot", "description": "Choose among an AI trading workspace, quantitative platform, broker API, or open-source framework by comparing the complete workflow.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "Automated trading buyer guide", "heading": "Choose the workflow, not just the backtest tool", "summary": "Start by deciding whether you need conversational research and trading, a complete AI strategy lifecycle, quantitative infrastructure, a broker API, or an open-source framework.", "primaryAction": { "label": "Start with BotSpot", "url": "/sales?showLogin=1" }, "secondaryAction": { "label": "Compare BotSpot and QuantConnect", "url": "/compare/botspot-vs-quantconnect" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "1. Decide what you want to do first", "bullets": [ "Research or trade conversationally: choose an AI agent with the data and approval tools you need.", "Build and operate algorithms: compare code generation, revisions, backtests, broker connections, and monitoring.", "Own quantitative infrastructure: compare engines, datasets, notebooks, optimization, and deployment controls.", "Build your own application: compare broker APIs, market access, authentication, and operational obligations." ] }, { "heading": "2. Ask who owns production operations", "paragraphs": [ "The largest difference is often who owns credentials, market data, scheduling, monitoring, retries, deployment safety, and incident response after a strategy moves beyond a backtest." ] }, { "heading": "3. Demand evidence you can inspect", "bullets": [ "Read official documentation and current integration lists.", "Inspect strategy code and assumptions before trusting a backtest. Treat backtests as simulations and include drawdown plus date range whenever you show a number.", "Distinguish simulated results from live history.", "Verify fees, data coverage, broker permissions, approval boundaries, and operational limits." ] }, { "heading": "Risk and suitability", "paragraphs": [ "Automated trading can lose money. Historical backtests do not guarantee future performance. Platform tooling does not replace strategy review, risk controls, broker due diligence, tax advice, legal advice, or investment advice." ] } ], "relatedLinks": [ { "label": "Compare BotSpot and QuantConnect", "url": "/compare/botspot-vs-quantconnect" }, { "label": "Use BotSpot with Alpaca", "url": "/compare/botspot-vs-alpaca" }, { "label": "Explore supported brokers", "url": "/brokers" }, { "label": "MCP for Agents", "url": "/agents" } ], "sources": [ { "label": "BotSpot public manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" }, { "label": "QuantConnect algorithm documentation", "url": "https://www.quantconnect.com/docs/v2/writing-algorithms" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides/how-to-build-an-ai-trading-bot", "url": "https://botspot.trade/guides/how-to-build-an-ai-trading-bot", "title": "How to Build an AI Trading Bot | BotSpot", "description": "Turn a trading idea into explicit rules, inspect AI-generated strategy code, backtest it, test it with paper trading, and prepare it for controlled deployment.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "Practical AI trading bot guide", "heading": "Build an AI trading bot from testable rules, not a vague prompt", "summary": "Define the decision your bot must make, use AI to turn that specification into an inspectable Lumibot strategy, test it against historical data, and validate its operations before putting capital at risk.", "primaryAction": { "label": "Start building in BotSpot", "url": "/ai-agent" }, "secondaryAction": { "label": "Read the backtesting guide", "url": "/guides/backtesting-ai-trading-strategies" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "1. Write the trading decision before asking AI for code", "paragraphs": [ "Begin with rules another person could follow without guessing. Name the asset universe, required data, evaluation schedule, entry condition, exit condition, position-sizing rule, and conditions that must block trading.", "A useful prompt describes observable inputs and actions. A request to build a bot that trades well does not define a testable strategy." ], "bullets": [ "Define which symbols or asset-selection rule the strategy may use.", "State when the strategy evaluates conditions and which timezone applies.", "Separate entry, exit, sizing, and risk rules.", "Describe what should happen when data is missing, stale, or invalid." ] }, { "heading": "2. Generate and inspect the strategy", "paragraphs": [ "Ask the BotSpot agent to turn the specification into a Lumibot strategy. Strategy state, lifecycle methods, parameters, data requests, and order behavior should remain visible for review.", "AI-generated code is a draft, not evidence that the strategy is correct. Map every generated rule back to the original specification before testing." ], "bullets": [ "Check symbol handling, market calendars, timezones, and evaluation timing.", "Inspect position sizing, order types, and duplicate-order protection.", "Look for hidden defaults and assumptions that were not in the prompt.", "Keep broker credentials in protected configuration, never prompts or public code." ] }, { "heading": "3. Run a backtest with declared assumptions", "paragraphs": [ "Choose a historical period and data source that fit the strategy. Record assumptions about execution, fees, slippage, liquidity, and missing data instead of treating defaults as facts.", "Verify that each input was available at the simulated decision time. Future information can make an impossible strategy appear convincing." ], "bullets": [ "Review trades and timestamps, not only summary performance.", "Confirm warm-up periods and indicators use past data only.", "Separate development periods from later out-of-sample checks.", "Investigate errors, zero-trade runs, and unexpectedly dense trading." ] }, { "heading": "4. Revise one hypothesis at a time", "paragraphs": [ "When a backtest exposes a problem, change one defined rule and record why. Rewriting several rules after every weak result makes learning difficult and increases overfitting risk.", "Use revisions to correct implementation errors, clarify rules, or test a stated alternative while preserving earlier results." ] }, { "heading": "5. Validate operations before live deployment", "paragraphs": [ "A backtest does not test credentials, broker permissions, network interruptions, rejected orders, delayed data, or monitoring. Use a supported paper account where available and observe the normal schedule.", "Before live use, verify broker support, account permissions, asset eligibility, order behavior, and the stop process. Paper and live modes vary by broker." ] }, { "heading": "Limitations and risk", "paragraphs": [ "AI can shorten the path from written rules to executable code, but it cannot prove the rules have an edge. Generated code can contain mistakes or unsafe assumptions.", "Backtests, simulations, and paper trading are hypothetical. Live results can differ because of latency, liquidity, slippage, fees, partial fills, market impact, outages, and changing market conditions." ] }, { "heading": "Build your workflow with live guidance", "paragraphs": [ "Want help moving from a trading idea to a working strategy? In the live AI Trading Bootcamp, Rob Grzesik teaches the workflow from AI research through bot building, backtesting and reviewing results. Explore the syllabus to see whether the course fits your next step." ], "links": [ { "label": "Explore the AI Trading Course & Live Bootcamp", "url": "/courses/ai-trading-bootcamp" } ] } ], "faq": [ { "question": "Do I need to know how to code to build an AI trading bot?", "answer": "You can start from plain-English rules and use BotSpot to generate and revise Lumibot code. You still need to inspect logic, assumptions, evidence, and deployment behavior." }, { "question": "Can a BotSpot strategy trade live?", "answer": "BotSpot supports automated strategy workflows through listed broker connections, subject to broker, mode, account permissions, asset eligibility, and current BotSpot support." }, { "question": "Will an AI-generated trading bot be profitable?", "answer": "No platform or backtest can guarantee profitability. Historical and simulated results are not predictive of future results." } ], "relatedLinks": [ { "label": "Backtest AI trading strategies", "url": "/guides/backtesting-ai-trading-strategies" }, { "label": "Compare paper and live trading", "url": "/guides/paper-trading-vs-live-trading" }, { "label": "Explore supported brokers", "url": "/brokers" }, { "label": "Use BotSpot through an MCP client", "url": "/agents" } ], "sources": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "BotSpot Terms of Service", "url": "/terms" }, { "label": "Lumibot lifecycle methods", "url": "https://lumibot.lumiwealth.com/lifecycle_methods.html" }, { "label": "Lumibot backtesting documentation", "url": "https://lumibot.lumiwealth.com/backtesting.html" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides/algorithmic-trading-without-coding", "url": "https://botspot.trade/guides/algorithmic-trading-without-coding", "title": "Algorithmic Trading Without Coding | BotSpot Guide", "description": "Learn how to describe trading rules in plain English, generate inspectable strategy code with AI, backtest it, and validate it without writing every line yourself.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "Plain-English algorithmic trading guide", "heading": "Build an algorithmic trading workflow without writing every line yourself", "summary": "Use conversation to define strategy rules, generate inspectable Lumibot code, test historical behavior, and prepare a supported broker workflow. No-code input reduces typing; it does not remove review, testing, or risk ownership.", "primaryAction": { "label": "Describe a strategy to BotSpot", "url": "/ai-agent" }, "secondaryAction": { "label": "See how AI bot building works", "url": "/guides/how-to-build-an-ai-trading-bot" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "1. Convert the idea into unambiguous rules", "paragraphs": [ "Plain English works best when it describes a system rather than a desired outcome. State what the strategy observes, when it evaluates, what causes an order, how large that order may be, and what closes or blocks a position.", "Avoid subjective phrases such as strong trend, safe entry, or good stock unless the prompt defines how each phrase is measured." ], "bullets": [ "Name the asset universe or selection process.", "Define indicators and exact parameters.", "Define entry and exit conditions separately.", "Set position, exposure, and trading-frequency constraints." ] }, { "heading": "2. Let the agent produce technical artifacts", "paragraphs": [ "BotSpot can turn the specification into a Lumibot strategy, revise the implementation, and run backtests. Users can work inside BotSpot or through a compatible MCP client.", "Ask for code plus a plain-English rule map that connects each requirement to its implementation." ] }, { "heading": "3. Review code even when you did not write it", "paragraphs": [ "Algorithmic trading without manual coding is not algorithmic trading without code. Generated code still controls scheduling, data use, order submission, and strategy state.", "Review the artifact or use a qualified reviewer. Ask for explanations of any lifecycle method or rule you cannot verify." ], "bullets": [ "Verify order sizing and duplicate-order safeguards.", "Inspect time comparisons, market calendars, and symbol formats.", "Confirm errors cannot silently turn into unintended orders.", "Never paste broker passwords, private keys, or API secrets into a prompt." ] }, { "heading": "4. Test the rules, not the story", "paragraphs": [ "Run historical tests using declared dates, data, and execution assumptions. Review individual trades rather than accepting a generated narrative about results.", "Do not repeatedly optimize until a preferred number appears. Preserve an out-of-sample period and record why each revision exists." ] }, { "heading": "5. Connect a broker only after understanding the workflow", "paragraphs": [ "BotSpot uses supported third-party brokers for eligible account and execution workflows. Current assets, paper or live modes, authentication methods, and warnings are published in the broker manifest.", "Confirm broker permissions, market data, fees, regional eligibility, and order support before paper or live operation." ] }, { "heading": "What no-code does not remove", "paragraphs": [ "Plain-English creation reduces syntax work. It does not remove ambiguity, data problems, software defects, broker constraints, market risk, or responsibility for deployed code." ] } ], "faq": [ { "question": "Is BotSpot truly no-code?", "answer": "BotSpot lets users start with plain-English instructions and generates inspectable strategy code. Review remains required because deployment decisions need more than a conversational description." }, { "question": "Which markets can a BotSpot strategy use?", "answer": "Available workflows depend on strategy, data, broker, account permissions, and current integration support. Broker pages list current connections and modes." }, { "question": "Can the agent place trades directly?", "answer": "When direct trading is enabled, BotSpot can prepare supported one-time trading actions for explicit user approval. Automated deployment is a separate workflow." } ], "relatedLinks": [ { "label": "Build an AI trading bot", "url": "/guides/how-to-build-an-ai-trading-bot" }, { "label": "Backtest AI trading strategies", "url": "/guides/backtesting-ai-trading-strategies" }, { "label": "Compare paper and live trading", "url": "/guides/paper-trading-vs-live-trading" }, { "label": "Explore supported brokers", "url": "/brokers" } ], "sources": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "BotSpot Terms of Service", "url": "/terms" }, { "label": "Lumibot lifecycle methods", "url": "https://lumibot.lumiwealth.com/lifecycle_methods.html" }, { "label": "Lumibot backtesting documentation", "url": "https://lumibot.lumiwealth.com/backtesting.html" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides/backtesting-ai-trading-strategies", "url": "https://botspot.trade/guides/backtesting-ai-trading-strategies", "title": "How to Backtest AI Trading Strategies | BotSpot", "description": "Build a defensible AI strategy backtest by freezing the hypothesis, checking data timing, documenting execution assumptions, and testing robustness.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "AI strategy backtesting guide", "heading": "Backtest an AI trading strategy without mistaking simulation for proof", "summary": "Freeze the hypothesis before testing, verify that historical inputs were available at each decision, inspect trades and assumptions, and reserve unseen data for robustness checks.", "primaryAction": { "label": "Backtest a strategy in BotSpot", "url": "/ai-agent" }, "secondaryAction": { "label": "Review BotSpot case studies", "url": "/case-studies" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "1. Freeze the hypothesis before running the test", "paragraphs": [ "Write what the strategy is expected to exploit and how the rules express that idea. Record universe, data inputs, entry and exit rules, sizing, schedule, and risk constraints before looking at results.", "This starting record prevents the strategy story from changing after every result." ] }, { "heading": "2. Check data timing and historical coverage", "paragraphs": [ "A valid simulation uses only information available at each historical decision point. Verify publication timing, bar completion, timezone handling, corporate actions, symbol history, and changing research universes.", "Missing or revised history should be documented, not silently replaced." ], "bullets": [ "Compare requested dates with actual data coverage.", "Check that indicators use completed historical observations.", "Look for delisted assets or changing universe membership.", "Investigate gaps instead of assuming missing data means no signal." ] }, { "heading": "3. Document the execution model", "paragraphs": [ "Every backtest assumes prices, fills, latency, fees, slippage, liquidity, partial fills, and market impact. Record what the test models and omits.", "Order timestamps and types must match a feasible live workflow." ] }, { "heading": "4. Read behavior behind summary performance", "paragraphs": [ "Do not judge a strategy from one return figure. Inspect trade list, drawdowns, exposure, turnover, concentration, holding periods, and dependence on a small number of events.", "Trace surprising results back to data and code before making performance claims." ] }, { "heading": "5. Test robustness without tuning away every failure", "paragraphs": [ "Reserve later or unseen data for out-of-sample testing. Vary reasonable dates and parameters to learn whether results depend on one narrow configuration.", "Record how many alternatives were tried and why the final configuration was chosen." ] }, { "heading": "6. Move from historical simulation to operational testing", "paragraphs": [ "Paper trading tests more of the live schedule, data connection, order construction, state management, and broker integration without real-money orders.", "Paper fills still remain simulations. Compare paper behavior with backtest expectations before any live decision." ] }, { "heading": "Limitations and risk", "paragraphs": [ "Backtests can be wrong because of bad data, look-ahead bias, overfitting, omitted costs, unrealistic fills, or defects. Even a careful historical test cannot predict future conditions." ] }, { "heading": "Practice backtesting with live guidance", "paragraphs": [ "Want help interpreting a backtest and improving your process? Learn the research, strategy-building and backtesting workflow live with Rob Grzesik in the AI Trading Bootcamp. Review the syllabus and course format before enrolling." ], "links": [ { "label": "Explore the AI Trading Course & Live Bootcamp", "url": "/courses/ai-trading-bootcamp" } ] } ], "faq": [ { "question": "How much historical data should an AI trading strategy use?", "answer": "No single period fits every strategy. Use enough relevant history to observe different conditions while respecting data availability and holding period. Reserve unseen data for evaluation." }, { "question": "Does a strong backtest mean a strategy is ready for live trading?", "answer": "No. Backtests do not validate live credentials, broker permissions, network behavior, market impact, or future performance." }, { "question": "Can AI optimize strategy parameters automatically?", "answer": "AI can explore parameters, but repeated tuning against one sample increases overfitting risk. Track tests and judge stability rather than the highest result." } ], "relatedLinks": [ { "label": "Understand backtesting metrics", "url": "/guides/backtesting-metrics-explained" }, { "label": "Avoid strategy overfitting", "url": "/guides/avoid-overfitting-trading-strategies" }, { "label": "Use walk-forward testing", "url": "/guides/walk-forward-testing-trading-strategies" }, { "label": "Prevent look-ahead bias and data leakage", "url": "/guides/look-ahead-bias-and-data-leakage" }, { "label": "Model slippage, fees, and market impact", "url": "/guides/modeling-slippage-fees-and-market-impact" }, { "label": "Build an AI trading bot", "url": "/guides/how-to-build-an-ai-trading-bot" }, { "label": "Compare paper and live trading", "url": "/guides/paper-trading-vs-live-trading" }, { "label": "Review complex backtest case studies", "url": "/case-studies" }, { "label": "Explore supported brokers", "url": "/brokers" } ], "sources": [ { "label": "BotSpot Terms of Service", "url": "/terms" }, { "label": "BotSpot case studies", "url": "/case-studies" }, { "label": "Lumibot backtesting documentation", "url": "https://lumibot.lumiwealth.com/backtesting.html" }, { "label": "Lumibot lifecycle methods", "url": "https://lumibot.lumiwealth.com/lifecycle_methods.html" }, { "label": "Alpaca paper trading documentation", "url": "https://docs.alpaca.markets/us/v1.4.2/docs/paper-trading" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides/paper-trading-vs-live-trading", "url": "https://botspot.trade/guides/paper-trading-vs-live-trading", "title": "Paper Trading vs Live Trading | BotSpot Guide", "description": "Compare paper and live algorithmic trading, learn what simulations can validate, and use a practical checklist before putting capital at risk.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "Trading deployment guide", "heading": "Paper trading vs live trading: know what each stage can prove", "summary": "Use backtests for historical logic, paper trading for operational rehearsal, and live trading only after a separate review of broker permissions, execution risk, monitoring, and capital exposure.", "primaryAction": { "label": "View supported broker modes", "url": "/brokers" }, "secondaryAction": { "label": "Read the backtesting guide", "url": "/guides/backtesting-ai-trading-strategies" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "1. Separate three different tests", "paragraphs": [ "Backtesting, paper trading, and live trading answer different questions. Treating them as interchangeable hides evidence gaps." ], "bullets": [ "Backtesting asks how coded rules behaved against historical data under a simulation model.", "Paper trading asks whether the strategy operates against current data and a simulated account workflow.", "Live trading exposes real capital to broker, exchange, liquidity, latency, fee, and market-impact conditions." ] }, { "heading": "2. Use paper trading to test operations", "paragraphs": [ "Paper trading can reveal scheduling mistakes, stale state, malformed orders, missing data, authentication problems, and monitoring gaps that historical tests miss.", "Observe trade and no-trade periods, reconnects, restarts, rejected actions, and agreement between strategy state and broker state." ] }, { "heading": "3. Know what paper fills cannot reproduce", "paragraphs": [ "Paper orders are simulated rather than routed to a live market. Systems may omit or approximate market impact, information leakage, latency slippage, queue position, price improvement, fees, dividends, or available liquidity.", "Paper results must remain labeled as simulated, never live performance." ] }, { "heading": "4. Verify connection and account requirements", "paragraphs": [ "BotSpot broker modes vary. Some connections support paper and live workflows; others are live-only. Authentication, assets, permissions, market data, fees, order eligibility, and regions also vary.", "Read the current BotSpot broker page and official broker documentation before connecting." ], "bullets": [ "Confirm broker, asset, and desired mode are listed.", "Verify account approval for intended products and order types.", "Check current market-data access and trading-session rules.", "Disable withdrawal permissions on API keys where applicable." ] }, { "heading": "5. Make live deployment a separate decision", "paragraphs": [ "Passing a paper test does not authorize live use. Review code, historical assumptions, paper observations, broker configuration, exposure constraints, and monitoring responsibility first.", "Define acceptable exposure, order constraints, escalation steps, and a stop process before deployment." ] }, { "heading": "6. Compare live behavior with paper expectations", "paragraphs": [ "After live deployment, compare real order timing, fills, fees, rejections, and position state with backtest and paper assumptions. Investigate differences instead of dismissing them as noise.", "Return to paper validation after material changes to logic, broker integration, data, credentials, scheduling, or infrastructure." ] }, { "heading": "Limitations and risk", "paragraphs": [ "Paper trading is useful for operational testing, but it does not predict live results. Live behavior can differ because of latency, slippage, liquidity, fees, partial fills, market impact, outages, and changing conditions." ] } ], "faq": [ { "question": "Does successful paper trading mean a bot is safe to run live?", "answer": "No. Paper trading validates parts of the workflow, but fills and account behavior remain simulated. It cannot prove profitability or live execution quality." }, { "question": "How long should a strategy paper trade before going live?", "answer": "No fixed duration proves readiness. Testing should cover normal schedule, trade and no-trade conditions, restarts, monitoring, and likely failure paths." }, { "question": "Do paper and live trading use the same broker credentials?", "answer": "That depends on the broker. Some use separate keys, accounts, or endpoints. Check the current broker page and official documentation." } ], "relatedLinks": [ { "label": "Explore supported broker modes", "url": "/brokers" }, { "label": "Backtest AI trading strategies", "url": "/guides/backtesting-ai-trading-strategies" }, { "label": "Build an AI trading bot", "url": "/guides/how-to-build-an-ai-trading-bot" }, { "label": "Use BotSpot with Alpaca", "url": "/brokers/alpaca" } ], "sources": [ { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "BotSpot Terms of Service", "url": "/terms" }, { "label": "Alpaca paper trading documentation", "url": "https://docs.alpaca.markets/us/v1.4.2/docs/paper-trading" }, { "label": "Alpaca Trading API documentation", "url": "https://docs.alpaca.markets/us/docs/trading-api" }, { "label": "Lumibot backtesting documentation", "url": "https://lumibot.lumiwealth.com/backtesting.html" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides/best-backtesting-software", "url": "https://botspot.trade/guides/best-backtesting-software", "title": "Best Backtesting Software by Trading Workflow | BotSpot", "description": "Compare backtesting software for AI-assisted, no-code, chart-based, code-first, and MQL5 workflows using documented features and limitations.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-14", "content": { "eyebrow": "Backtesting software buyer guide", "heading": "Best backtesting software depends on your strategy workflow", "summary": "No single backtester fits every trader. Match six products to the way you author strategies, source data, model execution, inspect results, and move toward paper or live operation. Recommendations are editorial workflow matches based on official documentation, not independent performance rankings.", "primaryAction": { "label": "Backtest a strategy in BotSpot", "url": "/ai-agent" }, "secondaryAction": { "label": "Learn defensible backtesting", "url": "/guides/backtesting-ai-trading-strategies" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "cards": [ { "eyebrow": "Workflow match: AI agent", "heading": "BotSpot", "summary": "For conversational strategy creation, inspectable Lumibot code, managed backtests, revisions, artifacts, and supported deployment workflows.", "url": "/ai-agent" }, { "eyebrow": "Workflow match: charts and Pine", "heading": "TradingView", "summary": "For chart-centered analysis, Pine Script strategies, built-in or community scripts, and visual Strategy Reports.", "url": "/compare/botspot-vs-tradingview" }, { "eyebrow": "Workflow match: no-code technical rules", "heading": "TrendSpider", "summary": "For natural-language or point-and-click technical strategies, visual testing, result analysis, and alert or bot workflows.", "url": "/compare/botspot-vs-trendspider" }, { "eyebrow": "Workflow match: portfolio rules", "heading": "Composer", "summary": "For AI-assisted or visual portfolio Symphonies, allocation logic, benchmark comparisons, and integrated automated execution.", "url": "/compare/botspot-vs-composer" }, { "eyebrow": "Workflow match: quantitative code", "heading": "QuantConnect", "summary": "For Python or C# research, LEAN algorithms, cloud or local testing, detailed result analysis, and quantitative deployment controls.", "url": "/compare/botspot-vs-quantconnect" }, { "eyebrow": "Workflow match: MQL5 robots", "heading": "MetaTrader 5", "summary": "For MQL5 Expert Advisors, broker-supplied history, tick-model choices, parameter optimization, and forward testing.", "url": "https://www.metatrader5.com/en/terminal/help/algotrading/testing" } ], "sections": [ { "heading": "How this guide selects and evaluates software", "paragraphs": [ "This guide includes six products with distinct documented approaches to strategy authoring, historical simulation, result inspection, and operational follow-through. Inclusion does not mean every product fits every asset, broker, region, frequency, or account.", "Workflow recommendations are editorial inferences from official product documentation reviewed on the verification date. BotSpot did not run a standardized independent benchmark of simulation accuracy, data quality, execution speed, or investment returns." ], "bullets": [ "No product receives a universal first-place ranking.", "Order reflects workflow variety, not performance.", "Current subscription prices are omitted because plans and entitlements change.", "Product claims remain attributed to official documentation rather than presented as independent test results.", "Users should verify current data, asset, broker, plan, and regional availability before choosing." ] }, { "heading": "What to compare before choosing a backtester", "bullets": [ "Strategy authoring: conversational AI, visual blocks, point-and-click conditions, Pine Script, Python, C#, or MQL5.", "Historical data: assets, resolution, corporate actions, symbol history, publication timing, and missing-data behavior.", "Execution model: order timing, prices, spreads, fees, slippage, latency, liquidity, partial fills, and market impact.", "Validation controls: out-of-sample periods, forward testing, parameter tracking, and reproducible configurations.", "Evidence: trades, timestamps, logs, charts, benchmarks, drawdowns, exposure, turnover, and downloadable artifacts.", "Operational continuity: paper trading, broker compatibility, monitoring, deployment, and comparison with live behavior." ] }, { "heading": "BotSpot: workflow match for AI-assisted strategy iteration", "paragraphs": [ "BotSpot adds a managed workflow around Lumibot. Users can describe rules conversationally, inspect generated strategy code, run and revise backtests, review charts, trades, logs, files, and audit history, then use supported broker connections for later paper or live workflows.", "This fit is strongest when strategy creation, backtest iteration, evidence review, and supported deployment should stay in one agent-led workspace." ], "bullets": [ "Authoring: conversational specification with inspectable Lumibot strategy code.", "Testing: managed historical runs using supported hosted data workflows.", "Evidence: generated artifacts, charts, trades, logs, files, and revision history.", "Watch: generated code and assumptions still require review; data and deployment options depend on current product and broker support." ] }, { "heading": "TradingView: workflow match for charts and Pine Script", "paragraphs": [ "TradingView strategies are Pine scripts that simulate hypothetical orders across historical and realtime chart bars. Built-in, community, and personal strategies can produce chart markers and a Strategy Report containing metrics and trade detail.", "This fit is strongest when charts, indicators, Pine Script, and visual inspection already anchor the research workflow." ], "bullets": [ "Authoring: Pine Script plus built-in and published community strategies.", "Testing: historical backtesting and realtime forward testing on chart data.", "Evidence: report metrics, trades, equity behavior, and chart markers.", "Watch: custom work requires Pine knowledge; synthetic prices on nonstandard charts can produce unrealistic results." ] }, { "heading": "TrendSpider: workflow match for no-code technical strategies", "paragraphs": [ "TrendSpider documents a Strategy Tester that accepts natural-language or point-and-click entry, exit, and risk rules. Optional custom JavaScript indicators can extend the visual workflow, and documented results include trade-level output and risk statistics.", "This fit is strongest for technical traders who want charts, conditions, testing, alerts, and bots without making general-purpose strategy code the main interface." ], "bullets": [ "Authoring: natural language, point-and-click conditions, or optional JavaScript indicators.", "Testing: visual rule testing across documented symbols, timeframes, and historical coverage.", "Evidence: trades, performance statistics, drawdown, and other strategy metrics.", "Watch: confirm current history depth, run limits, asset coverage, broker support, and plan entitlements for the intended workflow." ] }, { "heading": "Composer: workflow match for rules-based portfolio allocation", "paragraphs": [ "Composer represents strategies as editable Symphonies built with AI assistance or visual blocks for assets, weights, conditions, filters, and groups. Its product documentation shows benchmark comparisons, historical allocations, fees, slippage, and final-value modeling.", "This fit is strongest for investors building rules-based stock and ETF allocation or rebalancing strategies inside Composer’s integrated brokerage workflow." ], "bullets": [ "Authoring: AI-assisted creation or a no-code visual Symphony editor.", "Testing: portfolio backtests with benchmark and strategy comparisons.", "Evidence: performance metrics, historical allocation, modeled fees, and slippage.", "Watch: documented stock and ETF backtests use daily adjusted closing prices, which do not represent intraday market quotes." ] }, { "heading": "QuantConnect: workflow match for code-first quantitative research", "paragraphs": [ "QuantConnect runs LEAN algorithms through documented cloud, local, and command-line workflows. Projects support research, backtests, optimization, and live deployment, while result APIs and notebooks support deeper trade and chart analysis.", "This fit is strongest for developers and quantitative teams that want Python or C#, broad research controls, and explicit ownership of algorithm configuration." ], "bullets": [ "Authoring: Python or C# against the LEAN engine.", "Testing: cloud or local algorithm backtests with configurable data and models.", "Validation: documented out-of-sample holdouts and research guidance.", "Watch: coding and model configuration carry a learning curve; QuantConnect documents expected differences between backtest and live behavior." ] }, { "heading": "MetaTrader 5: workflow match for MQL5 Expert Advisors", "paragraphs": [ "MetaTrader 5 includes a Strategy Tester for MQL5 Expert Advisors and custom indicators. Official documentation covers multi-currency tests, parameter optimization, forward-period splits, tick-generation choices, visual tests, and execution-delay emulation.", "This fit is strongest when the strategy, broker, historical data, and deployment workflow already center on MetaTrader and MQL5." ], "bullets": [ "Authoring: MQL5 Expert Advisors and indicators.", "Testing: single runs, multi-parameter optimization, multiple tick modes, and visual testing.", "Validation: forward-period splits can separate parameter fitting from later checks.", "Watch: data and available symbols depend on the connected trading server; tick mode, delay, commission, margin, and symbol settings materially affect results." ] }, { "heading": "Backtesting software cannot prove a strategy will work live", "paragraphs": [ "Every product simulates history through data and execution assumptions. Results can fail because of look-ahead bias, overfitting, bad data, omitted costs, unrealistic fills, software defects, or market changes.", "Choose software that makes assumptions and trade behavior inspectable. Preserve unseen data, test current operations in paper mode where available, and treat live deployment as a separate risk decision." ] } ], "faq": [ { "question": "Which backtesting software is best for beginners?", "answer": "No universal beginner choice exists. BotSpot fits users who want an AI agent and inspectable generated code. TrendSpider emphasizes point-and-click technical rules. Composer emphasizes visual portfolio Symphonies. TradingView offers built-in strategies but custom strategies use Pine Script." }, { "question": "Which backtesting software supports Python?", "answer": "QuantConnect supports Python algorithms in a code-first quantitative platform. BotSpot generates and operates inspectable Lumibot strategies, and Lumibot is a Python framework. Compare managed workflow needs against direct code and infrastructure control." }, { "question": "Can I compare returns from two different backtesting platforms directly?", "answer": "Not safely without reconciling data, dates, corporate actions, order timing, prices, fees, slippage, benchmarks, and other assumptions. Composer explicitly notes that platforms can use different backtest assumptions." }, { "question": "Does backtesting software predict live trading results?", "answer": "No. Backtests are historical simulations. Data availability, execution, latency, liquidity, fees, market impact, outages, and future market conditions can produce different live results." }, { "question": "Should I choose a backtester before choosing a broker?", "answer": "Evaluate both together. Asset coverage, historical data, paper mode, order types, account permissions, and deployment support can determine whether a strategy can move beyond historical testing." } ], "relatedLinks": [ { "label": "Backtest AI trading strategies", "url": "/guides/backtesting-ai-trading-strategies" }, { "label": "Understand backtesting metrics", "url": "/guides/backtesting-metrics-explained" }, { "label": "Avoid strategy overfitting", "url": "/guides/avoid-overfitting-trading-strategies" }, { "label": "Choose an automated trading platform", "url": "/guides/automated-trading-platforms" }, { "label": "Compare AI trading platforms", "url": "/compare" } ], "sources": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "BotSpot Terms of Service", "url": "/terms" }, { "label": "Lumibot backtesting documentation", "url": "https://lumibot.lumiwealth.com/backtesting.html" }, { "label": "TradingView strategy documentation", "url": "https://www.tradingview.com/pine-script-docs/concepts/strategies/" }, { "label": "TrendSpider strategy development and backtesting", "url": "https://trendspider.com/product/strategy-development-and-backtesting-tools/" }, { "label": "Composer product overview", "url": "https://www.composer.trade/" }, { "label": "Composer backtest basics", "url": "https://help.composer.trade/article/67-backtest-basics" }, { "label": "QuantConnect backtesting documentation", "url": "https://www.quantconnect.com/docs/v2/cloud-platform/backtesting/getting-started" }, { "label": "QuantConnect live reconciliation documentation", "url": "https://www.quantconnect.com/docs/v2/writing-algorithms/live-trading/reconciliation" }, { "label": "MetaTrader 5 Strategy Tester documentation", "url": "https://www.metatrader5.com/en/terminal/help/algotrading/testing" } ], "verifiedAt": "2026-08-14" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides/backtesting-metrics-explained", "url": "https://botspot.trade/guides/backtesting-metrics-explained", "title": "Backtesting Metrics Explained: Sharpe, Drawdown and More | BotSpot", "description": "Learn how CAGR, volatility, Sharpe, Sortino, drawdown, win rate, profit factor, expectancy, and turnover describe a trading backtest.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-14", "content": { "eyebrow": "Backtest performance metrics", "heading": "Backtesting metrics explained without magic numbers", "summary": "Read return, risk, trade, and activity metrics together. Each describes one part of a historical simulation; none proves that a strategy will work live.", "primaryAction": { "label": "Backtest a strategy in BotSpot", "url": "/ai-agent" }, "secondaryAction": { "label": "Read the complete backtesting guide", "url": "/guides/backtesting-ai-trading-strategies" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "Start by documenting calculation conventions", "paragraphs": [ "A metric is interpretable only when its inputs and conventions are known. Record test dates, return frequency, simple or logarithmic returns, annualization factor, risk-free rate, minimum acceptable return, benchmark, and treatment of fees, slippage, dividends, cash, and open positions.", "Compare strategies using the same data window and calculation method. Two platforms can show different values for the same equity curve because their sampling, annualization, trade grouping, or cost assumptions differ." ], "bullets": [ "State whether results use gross or net returns.", "State whether calculations use daily, weekly, monthly, or trade-level observations.", "State how break-even trades and open positions are treated.", "Keep percentage, currency, and per-trade metrics clearly separated." ] }, { "heading": "CAGR: compounded growth across the full test", "paragraphs": [ "Compound annual growth rate expresses the constant annual return that would connect starting portfolio value with ending portfolio value. For a test lasting T years, CAGR = (ending value / starting value)^(1 / T) - 1.", "CAGR accounts for compounding but ignores the path between endpoints. Two strategies can have the same CAGR while experiencing very different volatility, drawdowns, capital exposure, and recovery times.", "CAGR becomes misleading when a test contains external deposits or withdrawals. It is undefined or unsuitable when portfolio values needed by the formula are not positive." ] }, { "heading": "Volatility: variability of periodic returns", "paragraphs": [ "Historical volatility is usually calculated as the standard deviation of periodic returns. A common annualized estimate is volatility = standard deviation of periodic returns × square root of periods per year.", "That square-root annualization is a model convention, not a law. Serial correlation, irregular sampling, stale prices, and changing volatility can make it unreliable.", "Volatility treats upside and downside variation alike. It does not directly measure maximum loss, tail risk, liquidity, or time spent below a previous peak." ] }, { "heading": "Sharpe ratio: excess return per unit of total variability", "paragraphs": [ "For periodic observations, Sharpe ratio = mean portfolio return minus matching risk-free return, divided by standard deviation of excess returns. A common annualization multiplies the periodic ratio by the square root of periods per year.", "Higher values indicate more historical excess return relative to measured variability under the chosen inputs. No universal cutoff makes a strategy good, safe, or deployable.", "Sharpe estimates can change materially with test dates, sampling frequency, risk-free rate, outliers, and serial correlation. Publish those inputs rather than presenting the ratio alone." ] }, { "heading": "Sortino ratio: return relative to downside deviation", "paragraphs": [ "Sortino ratio replaces total standard deviation with downside deviation below a selected minimum acceptable return. One common form is Sortino = (mean return - minimum acceptable return) / downside deviation.", "A common downside-deviation calculation is the square root of the average squared shortfall: sqrt(mean(minimum of 0 and return minus target, squared)). Exact denominator and annualization conventions vary.", "Sortino does not penalize returns above the target, making it useful beside Sharpe when return distributions are asymmetric. It still depends on sample quality, selected target, and reliable pricing." ] }, { "heading": "Maximum drawdown: worst observed peak-to-trough decline", "paragraphs": [ "At each point, drawdown compares current portfolio value with its previous high. Maximum drawdown = maximum over time of 1 - current value / highest earlier value.", "Maximum drawdown describes the deepest historical decline in the selected test. It does not show how often drawdowns occurred, how long recovery took, or whether a worse decline can occur later.", "Inspect drawdown duration and time under water beside maximum depth. A brief decline and a multi-year recovery can share the same maximum-drawdown percentage." ] }, { "heading": "Win rate: frequency, not magnitude", "paragraphs": [ "Win rate = number of profitable closed trades / total closed trades. State whether break-even trades remain in the denominator and whether fees are deducted before classifying each trade.", "A high win rate can coexist with an overall loss when losing trades are much larger than winning trades. A low win rate can coexist with positive historical results when occasional gains outweigh frequent smaller losses." ] }, { "heading": "Profit factor: gross gains relative to gross losses", "paragraphs": [ "Profit factor = sum of profits from winning closed trades / absolute sum of losses from losing closed trades. Use realized, net-of-modeled-cost trade results and disclose whether open positions are excluded.", "A value above 1 means gross winning-trade profit exceeded gross losing-trade loss within that sample and calculation. It does not reveal drawdown, timing, capital required, result stability, or dependence on one outlier.", "Profit factor is undefined or convention-dependent when no losing trades occur. Small trade counts can produce unstable values." ] }, { "heading": "Expectancy: average result per completed trade", "paragraphs": [ "Trade expectancy can be written as probability of a win × average win minus probability of a loss × average absolute loss. When all closed trades are classified consistently, it also equals total net profit or loss / number of closed trades.", "Label whether expectancy is expressed in currency, percentage return, or units of initial risk. A positive historical expectancy describes the tested sample, not a guaranteed future payoff.", "Inspect distribution and sample size. One extreme trade can raise average expectancy while the typical trade remains weak." ] }, { "heading": "Turnover: how much portfolio value changes hands", "paragraphs": [ "Turnover definitions vary. One established annual convention is turnover = lesser of security purchases or sales / average portfolio value. Other systems estimate the percentage of portfolio value replaced or sum position-weight changes.", "Publish the exact convention. Turnover is not interchangeable with trade count because one large rebalance and many small trades can produce different activity profiles.", "Higher turnover creates more exposure to commissions, spread, slippage, market impact, taxes, and operational failures. Those costs must be modeled separately rather than inferred from turnover alone." ] }, { "heading": "Read metrics as a system", "bullets": [ "CAGR describes compounded endpoint growth.", "Volatility describes return variability.", "Sharpe and Sortino relate return to selected risk measures.", "Maximum drawdown describes worst observed historical decline.", "Win rate, profit factor, and expectancy describe closed-trade outcomes.", "Turnover describes activity and potential execution burden.", "Trade list, equity curve, exposure, costs, and benchmark supply context that summary metrics omit." ] }, { "heading": "Limitations and risk", "paragraphs": [ "Every value on this page is an estimate from historical observations and simulation rules. Bad data, look-ahead bias, overfitting, omitted costs, unrealistic fills, and software defects can make precise-looking metrics wrong.", "Review multiple periods and market conditions, preserve out-of-sample data, inspect individual trades, and compare paper behavior with backtest assumptions. Historical metrics cannot predict future returns or maximum losses." ] } ], "faq": [ { "question": "What is a good Sharpe ratio for a backtest?", "answer": "No universal threshold proves quality. Interpretation depends on return frequency, risk-free rate, test length, costs, asset class, leverage, liquidity, and serial correlation. Compare consistently calculated values and inspect underlying returns." }, { "question": "Should I use Sharpe or Sortino ratio?", "answer": "Use both when available. Sharpe measures return relative to total variability; Sortino focuses on shortfalls below a chosen target. Neither replaces drawdown, trade distribution, or execution analysis." }, { "question": "Can a strategy have a high win rate and still lose money?", "answer": "Yes. Win rate counts profitable trades but ignores their size. A few large losses can outweigh many small gains." }, { "question": "Why do backtesting platforms report different metrics?", "answer": "Platforms may use different return frequencies, annualization factors, risk-free rates, trade grouping, fee models, open-position treatment, and turnover definitions. Compare formulas and inputs before comparing values." }, { "question": "Does positive expectancy predict future profit?", "answer": "No. Positive expectancy summarizes average results in the tested sample. Future data, fills, costs, liquidity, and market conditions can differ." } ], "relatedLinks": [ { "label": "Complete AI strategy backtesting guide", "url": "/guides/backtesting-ai-trading-strategies" }, { "label": "Avoid overfitting trading strategies", "url": "/guides/avoid-overfitting-trading-strategies" }, { "label": "Use walk-forward testing", "url": "/guides/walk-forward-testing-trading-strategies" }, { "label": "Model slippage, fees, and market impact", "url": "/guides/modeling-slippage-fees-and-market-impact" }, { "label": "Compare paper and live trading", "url": "/guides/paper-trading-vs-live-trading" } ], "sources": [ { "label": "CFA Institute: 60/40 portfolio performance metric formulas", "url": "https://rpc.cfainstitute.org/sites/default/files/docs/research-reports/monash-report-1_performance-of-the-6040_online.pdf" }, { "label": "CFA Institute: The Statistics of Sharpe Ratios", "url": "https://rpc.cfainstitute.org/research/financial-analysts-journal/2002/the-statistics-of-sharpe-ratios" }, { "label": "CFA Institute: The Sortino Ratio", "url": "https://rpc.cfainstitute.org/-/media/documents/code/gips/the-sortino-ratio.pdf" }, { "label": "QuantConnect backtest report statistics", "url": "https://www.quantconnect.com/docs/v2/cloud-platform/backtesting/report" }, { "label": "QuantConnect backtest statistics reference", "url": "https://www.quantconnect.com/docs/v2/cloud-platform/api-reference/backtest-management/read-backtest/backtest-statistics" }, { "label": "TradingView profit factor definition", "url": "https://www.tradingview.com/support/solutions/43000681698-profit-factor/" }, { "label": "TradingView percent-profitable definition", "url": "https://www.tradingview.com/support/solutions/43000681714-percent-profitable/" }, { "label": "TradingView expected-payoff definition", "url": "https://www.tradingview.com/support/solutions/43000772770-expected-payoff/" }, { "label": "SEC Form N-1A portfolio-turnover calculation", "url": "https://www.sec.gov/files/form-n-1a.pdf" }, { "label": "FINRA investment-return calculations", "url": "https://www.finra.org/investors/insights/investment-returns" } ], "verifiedAt": "2026-08-14" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides/avoid-overfitting-trading-strategies", "url": "https://botspot.trade/guides/avoid-overfitting-trading-strategies", "title": "How to Avoid Overfitting a Trading Strategy | BotSpot", "description": "Reduce backtest overfitting by logging every trial, separating strategy selection from evaluation, preserving unseen data, and testing parameter robustness.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-14", "content": { "eyebrow": "Trading strategy validation guide", "heading": "Avoid overfitting a trading strategy before strong backtest results mislead you", "summary": "Control the full research process: define the hypothesis and search space first, log every variant, keep strategy selection separate from final evaluation, and prefer stable behavior over one winning configuration.", "primaryAction": { "label": "Backtest a strategy in BotSpot", "url": "/ai-agent" }, "secondaryAction": { "label": "Read the backtesting guide", "url": "/guides/backtesting-ai-trading-strategies" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "1. Treat strategy search as part of the backtest", "paragraphs": [ "Overfitting does not require an obviously complex model. It can happen when a researcher tries many indicators, parameters, universes, date ranges, filters, or scoring rules and then reports the strongest historical result.", "The selected strategy may fit repeatable structure, historical noise, or both. A smooth equity curve cannot distinguish them by itself." ], "bullets": [ "Performance depends on one narrow parameter value or date range.", "Most gains come from a small number of trades or market episodes.", "Small rule changes produce large performance changes.", "The strategy performs well only in the sample used to choose it." ] }, { "heading": "2. Freeze the research protocol before searching", "paragraphs": [ "Write the economic or behavioral hypothesis before viewing optimized results. Define what evidence would support it, what evidence would reject it, and which choices the search may change.", "Set a research budget. A search with explicit bounds is easier to evaluate than an open-ended loop that stops when an attractive result appears." ], "bullets": [ "Declare the asset universe, historical dates, benchmark, and data source.", "Choose the primary evaluation metric before ranking variants.", "List permitted indicators, parameter ranges, filters, and position-sizing rules.", "Set minimum trade count, exposure, liquidity, and risk constraints.", "Define stopping criteria and preserve rejected variants in the experiment log." ] }, { "heading": "3. Separate strategy selection from final evaluation", "paragraphs": [ "Use earlier data for development, later data for validation, and a final untouched period for evaluation. Keep every split chronological because random splitting can train on future observations and evaluate on earlier ones.", "A holdout period stops being untouched when its result influences another rule, parameter, or feature choice. Move that period into the research record and obtain new evidence instead of continuing to call it a final test.", "One holdout is not a complete cure. Research on investment backtests shows that broad strategy selection can still overfit finite historical samples, especially when the same history supports many decisions." ], "bullets": [ "Never optimize directly against the final holdout.", "Use time-aware splits and an appropriate gap when observations or labels overlap.", "Keep data preparation and feature-selection decisions inside the development process.", "Record every time validation evidence causes a strategy revision." ] }, { "heading": "4. Count every trial, including discarded ideas", "paragraphs": [ "Testing more alternatives raises the chance that one looks successful through chance. Trial count includes more than explicit parameter combinations: changing universes, date windows, indicators, filters, objectives, or benchmarks also creates selection opportunities.", "Record the complete search family. When statistical claims matter, use methods designed for multiple testing or selection bias rather than interpreting the winning unadjusted metric as if it were the only strategy tested." ], "bullets": [ "Assign each run an immutable identifier and store its full configuration.", "Log failed runs and manual revisions, not only saved strategies.", "Report search size and selection rule beside the chosen result.", "Distinguish exploratory findings from confirmatory tests.", "Use formal corrections only when their assumptions and required inputs are understood." ] }, { "heading": "5. Prefer stable regions over one parameter peak", "paragraphs": [ "Inspect nearby parameter values rather than selecting only the historical maximum. A strategy whose behavior remains similar across a reasonable neighborhood provides stronger robustness evidence than one that works at one exact threshold.", "Repeat sensitivity checks across different start dates, subperiods, market conditions, and eligible universes. CFA Institute guidance treats sensitivity and scenario analysis as complements to historical backtesting because one observed history cannot represent every possible future." ], "bullets": [ "Plot results across the parameter surface instead of showing one winner.", "Compare performance distribution across periods, not only aggregate performance.", "Check whether conclusions survive reasonable changes to assumptions.", "Investigate why unstable regions fail before adding more parameters." ] }, { "heading": "6. Reduce unnecessary degrees of freedom", "paragraphs": [ "Every additional parameter, filter, exception, or model branch creates another way to fit historical noise. Complexity should earn its place through a stated mechanism and better validation evidence, not only a stronger development backtest.", "When a test fails, return to the hypothesis. Repeatedly adding exceptions until the same historical sample passes converts evaluation data into training data." ], "bullets": [ "Prefer explicit rules with fewer independently tuned choices.", "Remove features whose role cannot be explained or validated.", "Compare complex candidates against simple benchmarks.", "Require material, stable improvement before retaining extra complexity." ] }, { "heading": "7. Report evidence without hiding the search process", "paragraphs": [ "Publish the hypothesis, data periods, benchmark, primary metric, number of trials, selected configuration, nearby configurations, and limitations. Reporting only the best run hides information needed to judge selection bias.", "Move surviving strategies to walk-forward and paper testing. These stages add evidence about changing data and operational behavior, but neither proves future profitability." ] }, { "heading": "Limitations and risk", "paragraphs": [ "No holdout, cross-validation method, robustness check, or multiple-testing adjustment can guarantee live performance. Financial samples are finite, observations can be dependent, and market structure can change.", "Formal measures such as Probability of Backtest Overfitting and Deflated Sharpe Ratio require assumptions, sufficient observations, and a defensible record of the strategies tested. They should support judgment, not become another number to optimize." ] } ], "faq": [ { "question": "How many strategy parameters are too many?", "answer": "No universal cutoff exists. Risk depends on sample size, parameter ranges, dependence between trials, strategy complexity, and total search breadth. Track every free choice and require each added parameter to improve unseen evidence, not only development results." }, { "question": "Does good out-of-sample performance prove a strategy is not overfit?", "answer": "No. It provides stronger evidence only when the sample remained untouched during selection. Repeatedly checking and reacting to the same out-of-sample period turns it into development data." }, { "question": "Should I select the strategy with the highest Sharpe ratio?", "answer": "Not by itself. The highest observed Sharpe ratio can reflect selection from many trials, non-normal returns, or dependence on a narrow period. Review search count, robustness, drawdowns, trade behavior, and untouched evaluation evidence." }, { "question": "Can AI optimization increase overfitting risk?", "answer": "Yes. AI can generate and test more alternatives faster, increasing selection opportunities. Bound the search, preserve an experiment log, and keep final evaluation data outside the optimization loop." } ], "relatedLinks": [ { "label": "Backtest AI trading strategies", "url": "/guides/backtesting-ai-trading-strategies" }, { "label": "Understand backtesting metrics", "url": "/guides/backtesting-metrics-explained" }, { "label": "Use walk-forward testing", "url": "/guides/walk-forward-testing-trading-strategies" }, { "label": "Prevent look-ahead bias and data leakage", "url": "/guides/look-ahead-bias-and-data-leakage" }, { "label": "Model slippage, fees, and market impact", "url": "/guides/modeling-slippage-fees-and-market-impact" } ], "sources": [ { "label": "Probability of Backtest Overfitting research", "url": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2326253" }, { "label": "A Reality Check for Data Snooping", "url": "https://doi.org/10.1111/1468-0262.00152" }, { "label": "Multiple testing in expected-return research", "url": "https://www.nber.org/papers/w20592" }, { "label": "Deflated Sharpe Ratio research", "url": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2460551" }, { "label": "Model-selection overfitting research", "url": "https://www.jmlr.org/papers/v11/cawley10a.html" }, { "label": "CFA Institute backtesting and simulation", "url": "https://www.cfainstitute.org/insights/professional-learning/refresher-readings/2026/backtesting-and-simulation" }, { "label": "scikit-learn time-series cross-validation", "url": "https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html" } ], "verifiedAt": "2026-08-14" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides/walk-forward-testing-trading-strategies", "url": "https://botspot.trade/guides/walk-forward-testing-trading-strategies", "title": "Walk-Forward Testing for Trading Strategies | BotSpot", "description": "Learn how walk-forward testing uses ordered training and test windows to evaluate trading strategies while reducing leakage and overfitting risk.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-14", "content": { "eyebrow": "Trading strategy validation guide", "heading": "Use walk-forward testing to measure repeated out-of-sample behavior", "summary": "Define a sequence of historical training and test windows, fit or select strategy rules using only each training window, and evaluate the unchanged result on the period that follows. Walk-forward evidence can expose instability, but it cannot prove future performance.", "primaryAction": { "label": "Plan a strategy test in BotSpot", "url": "/ai-agent" }, "secondaryAction": { "label": "Read the backtesting guide", "url": "/guides/backtesting-ai-trading-strategies" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "1. Understand what moves forward", "paragraphs": [ "Walk-forward testing evaluates a strategy through multiple time-ordered folds. Each fold uses an earlier period for development and the next period for evaluation. The process then advances through history without training on future observations.", "Walk-forward testing and walk-forward optimization are related but not identical. Testing can evaluate fixed rules across sequential periods. Optimization adds parameter or model selection inside each training window before applying the selected version to the following test window." ], "bullets": [ "Fold 1: train on A–C, then test on D.", "Fold 2: train on an allowed window ending at D, then test on E.", "Fold 3: train on an allowed window ending at E, then test on F.", "Only test-period results count as out-of-sample evidence." ] }, { "heading": "2. Freeze the protocol before reading results", "paragraphs": [ "Choose the training length, test length, step size, optional gap, parameter search space, selection objective, execution model, and stopping rule before comparing outcomes. Changing the protocol after seeing weak folds turns the evaluation process into another optimization.", "Test-window length should reflect the intended live decision and retraining schedule. A model intended to update monthly should not claim deployment realism from a schedule that reselects parameters every day." ], "bullets": [ "Record every candidate rule and parameter range.", "Use the same data definitions, fees, slippage, and order assumptions across folds.", "Define minimum sample or trade requirements before excluding a fold.", "Preserve run history, including failed and zero-trade results." ] }, { "heading": "3. Choose anchored or rolling training windows", "paragraphs": [ "An anchored, or expanding, window keeps the original start date and adds newly available history at each step. It provides more training observations over time, but old regimes continue influencing every later fit.", "A rolling, or sliding, window moves both boundaries forward and keeps a fixed lookback length. It emphasizes recent history and discards older observations, but gives each fit less data.", "Neither design is universally better. Choose one based on how the deployed strategy would learn and how quickly its inputs may become stale, then keep that choice fixed during evaluation." ], "bullets": [ "Anchored: train A–C → D; train A–D → E; train A–E → F.", "Rolling: train A–C → D; train B–D → E; train C–E → F.", "Use equal test durations when comparing fold metrics based on elapsed time.", "Document warm-up data separately from observations eligible for fitting." ] }, { "heading": "4. Keep each fold free from future information", "paragraphs": [ "Fit normalization, feature selection, imputation, model parameters, thresholds, and universe rules using the training window only. Apply the fitted process to the next test window without learning from that window first.", "Add a gap between training and testing when labels, delayed publications, holding periods, or feature calculations overlap the boundary. A gap cannot repair incorrectly timestamped or revised data; inputs still need point-in-time availability.", "Earlier test observations may become training data in later folds because they would be known by that later date. They must not influence the earlier fold." ], "bullets": [ "Keep rows in chronological order; do not use random train-test splits.", "Timestamp inputs when they became available, not only when their reporting period ended.", "Build each historical universe from point-in-time membership.", "Do not preprocess the complete dataset before creating folds.", "Avoid overlapping test windows or account for duplicate dates when combining results." ] }, { "heading": "5. Reproduce the intended live update policy", "paragraphs": [ "When parameters change between folds, record which training observations, candidate values, objective, and tie-breaking rule selected each version. The version chosen from one training window must remain unchanged throughout its next test window.", "Frequent optimization can react to newer data, but it also increases compute, turnover, and opportunities to fit noise. QuantConnect documents this tradeoff between recent fitting and overfitting risk.", "A production implementation must reproduce historical retraining timing, data availability, warm-up, and state transitions. A walk-forward backtest that updates at impossible times does not represent a deployable process." ] }, { "heading": "6. Interpret the full out-of-sample sequence", "paragraphs": [ "Join non-overlapping test periods in chronological order to inspect the simulated experience produced by the complete update policy. Also report each fold separately so one exceptional interval cannot hide instability.", "Compare results with a relevant benchmark over the same dates and under compatible exposure and cost assumptions. Review drawdown, turnover, concentration, trade count, parameter changes, and execution sensitivity alongside returns." ], "bullets": [ "Report aggregate out-of-sample results, never the selected in-sample score as validation.", "Show fold dispersion, weak periods, and worst drawdown instead of only an average.", "Inspect whether chosen parameters remain stable or jump between extremes.", "Check whether results depend on one asset, trade, fold, or market regime.", "If walk-forward results guide another revision, label them development evidence and reserve a new final holdout or prospective paper period." ] }, { "heading": "Limits of walk-forward evidence", "paragraphs": [ "Walk-forward testing reduces some weaknesses of one historical split, but it does not eliminate selection bias. Trying many strategies, window designs, objectives, or preprocessing choices can overfit the complete research process.", "Short windows can produce noisy estimates. Long windows can mix incompatible regimes. Historical folds still depend on data quality and assumptions about fills, fees, slippage, liquidity, latency, partial fills, and market impact.", "Future market structure can differ from every historical window. Walk-forward results remain simulated and do not guarantee profitability, safe deployment, or live execution quality." ] } ], "faq": [ { "question": "Is walk-forward testing the same as walk-forward optimization?", "answer": "No. Walk-forward testing describes sequential, time-ordered evaluation. Walk-forward optimization additionally selects parameters or logic inside each training window before testing the selected version on the next period." }, { "question": "Should I use an anchored or rolling training window?", "answer": "Use the design that matches the intended live learning policy. Anchored windows retain all earlier history; rolling windows keep a fixed recent lookback. Choose before reviewing results and document the tradeoff." }, { "question": "How many walk-forward folds should a strategy use?", "answer": "No fixed number proves validity. Use enough chronological folds to evaluate repeated behavior while keeping each training and test window meaningful for the strategy frequency, sample size, and intended update schedule." }, { "question": "Does a successful walk-forward test mean a strategy is ready for live trading?", "answer": "No. Results remain historical simulations. Paper testing, broker validation, monitoring, exposure controls, and separate live-deployment review remain necessary." } ], "relatedLinks": [ { "label": "Backtest AI trading strategies", "url": "/guides/backtesting-ai-trading-strategies" }, { "label": "Understand backtesting metrics", "url": "/guides/backtesting-metrics-explained" }, { "label": "Avoid strategy overfitting", "url": "/guides/avoid-overfitting-trading-strategies" }, { "label": "Prevent look-ahead bias and leakage", "url": "/guides/look-ahead-bias-and-data-leakage" }, { "label": "Compare paper and live trading", "url": "/guides/paper-trading-vs-live-trading" } ], "sources": [ { "label": "BotSpot Terms of Service", "url": "/terms" }, { "label": "Lumibot backtesting documentation", "url": "https://lumibot.lumiwealth.com/backtesting.html" }, { "label": "QuantConnect walk-forward optimization", "url": "https://www.quantconnect.com/docs/v2/writing-algorithms/optimization/walk-forward-optimization" }, { "label": "QuantConnect optimization parameters and look-ahead bias", "url": "https://www.quantconnect.com/docs/v2/writing-algorithms/optimization/parameters" }, { "label": "scikit-learn TimeSeriesSplit documentation", "url": "https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html" }, { "label": "scikit-learn data leakage guidance", "url": "https://scikit-learn.org/stable/common_pitfalls.html#data-leakage" }, { "label": "sktime expanding-window documentation", "url": "https://www.sktime.net/docs/api-reference/sktimesplitexpandingwindowexpandingwindowsplitter/" }, { "label": "sktime sliding-window documentation", "url": "https://www.sktime.net/models/slidingwindowsplitter/" } ], "verifiedAt": "2026-08-14" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides/look-ahead-bias-and-data-leakage", "url": "https://botspot.trade/guides/look-ahead-bias-and-data-leakage", "title": "Look-Ahead Bias and Data Leakage in Backtests | BotSpot", "description": "Learn how point-in-time data, historical universes, filing timestamps, corporate actions, and indicator alignment prevent false backtest results.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-14", "content": { "eyebrow": "Backtest data-integrity guide", "heading": "Stop future information from leaking into your backtest", "summary": "Reconstruct what your strategy could have known at each decision time. Point-in-time datasets, historical universes, release timestamps, consistent corporate-action handling, and correctly aligned indicators prevent impossible signals from appearing valid.", "primaryAction": { "label": "Backtest a strategy in BotSpot", "url": "/ai-agent" }, "secondaryAction": { "label": "Read the complete backtesting guide", "url": "/guides/backtesting-ai-trading-strategies" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "1. Distinguish look-ahead bias from data leakage", "paragraphs": [ "Look-ahead bias occurs when a historical decision uses information that was unavailable at that decision time. Data leakage is broader: evaluation data influences strategy construction, feature preparation, parameter selection, or model training.", "Every input needs at least two clocks: when the underlying event occurred and when the value became available to the strategy. A reporting period end, market-data timestamp, database timestamp, and public release time may describe different moments." ], "bullets": [ "Event time: when the trade, accounting period, or corporate event occurred.", "Availability time: when the strategy could first receive and use the information.", "Decision time: when strategy logic evaluated available inputs.", "Execution time: earliest modeled time when resulting order could trade." ] }, { "heading": "2. Reconstruct point-in-time information", "paragraphs": [ "A current database snapshot can contain corrected prices, revised fundamentals, renamed symbols, and today's index members. Querying that snapshot by historical date does not automatically recreate the information available then.", "Use point-in-time records keyed by availability time. Preserve dataset version, source, timezone, revision identifier, and ingestion rule so another test can reconstruct the same information set." ], "bullets": [ "Reject any feature whose availability time is later than the simulated decision.", "Apply a documented reporting lag when reliable point-in-time timestamps are unavailable.", "Version datasets instead of silently replacing corrected history.", "Record whether missing values were genuinely unavailable or introduced during collection." ] }, { "heading": "3. Use historical universes, not today's survivors", "paragraphs": [ "Testing old periods against securities that exist today excludes many delisted companies and can use index membership learned after the fact. This survivorship bias changes both candidate selection and measured results.", "Rebuild the eligible universe at each historical date. Include delistings, historical constituents, ticker changes, listing dates, and securities that later failed whenever the strategy could have selected them." ], "bullets": [ "Do not apply today's S&P 500 or exchange list to earlier dates.", "Track stable security identifiers across ticker and company-name changes.", "Model delisting events and final position treatment.", "Confirm data coverage includes removed assets, not only active symbols." ] }, { "heading": "4. Delay fundamentals until publication", "paragraphs": [ "Financial values belong to a reporting period but are not knowable on that period's end date. A quarterly result should enter the simulation only after its filing or release became publicly available.", "Amended filings, restatements, and vendor revisions need separate availability timestamps. Do not replace an original value with its latest revision throughout earlier history." ], "bullets": [ "Store period end, filing form, accession number, acceptance time, and amendment status.", "Use the original filing value until a later amendment becomes available.", "Apply market-hours rules when information arrives after the close.", "Document vendor processing delay when provider availability trails public release." ] }, { "heading": "5. Align bars, indicators, signals, and orders", "paragraphs": [ "Bar timestamps require explicit interpretation. Alpaca, for example, timestamps a minute bar at the left edge of its interval, while the complete high, low, close, and volume are known only after that interval finishes.", "Compute indicators from completed observations. Unless an intrabar model supplies information available before the close, a signal using a bar's closing value cannot also receive that same closing price as an instantaneous fill." ], "bullets": [ "Define exchange timezone, daylight-saving behavior, session calendar, and extended-hours policy.", "Assert that every indicator input ends at or before the decision time.", "Shift signals to the next feasible execution event when they depend on completed bars.", "Keep warm-up observations before the test period from contributing trades or results.", "Inspect rolling-window and resampling boundaries for accidental forward fills." ] }, { "heading": "6. Handle corporate actions consistently", "paragraphs": [ "Splits, dividends, spin-offs, symbol changes, and delistings affect prices, holdings, indicators, and cash. Raw and adjusted datasets answer different questions; mixing them can create false signals or double-count returns.", "Choose and document one normalization policy for each calculation. If total-return-adjusted prices already incorporate dividends, adding the same dividends as separate cash flows can count them twice." ], "bullets": [ "Verify price and volume adjustment choices together.", "Test split dates for discontinuities in indicators and position quantities.", "Keep historical symbol mappings without rewriting earlier identity.", "Confirm benchmark and strategy returns use compatible dividend treatment.", "Reset or warm up live indicators when normalization differs around corporate events." ] }, { "heading": "7. Fit preprocessing inside each training window", "paragraphs": [ "Machine-learning leakage can occur before model fitting. Scaling, imputation, feature selection, dimensionality reduction, and threshold selection must not learn from evaluation periods.", "Split chronologically before fitting transforms. During walk-forward evaluation, fit every learned preprocessing step again using only the current training window, then transform the later evaluation window without refitting." ], "bullets": [ "Never fit normalization statistics on the full historical sample.", "Keep future labels separate from features used at decision time.", "Perform feature selection inside each training fold.", "Preserve unseen evaluation data until model and workflow choices are frozen." ] }, { "heading": "Backtest leakage checklist", "bullets": [ "Can every input be traced to source and first-available timestamp?", "Does an automated assertion enforce feature time less than or equal to decision time?", "Does universe history include prior constituents, ticker changes, and delistings?", "Are original and amended fundamental values available as separate vintages?", "Do completed-bar signals execute no earlier than their first feasible trade?", "Are raw, split-adjusted, dividend-adjusted, and total-return series used consistently?", "Are preprocessing steps fitted only on each training window?", "Can one sample trade be replayed using only records visible at that moment?", "Are data version, timezone, calendar, normalization, and reporting-lag rules saved with results?" ] }, { "heading": "Limitations and risk", "paragraphs": [ "Passing these checks does not prove a strategy has an edge. Historical datasets can still contain errors, missing observations, vendor-specific corrections, or timestamps that do not represent real delivery latency.", "Treat unexpectedly strong results as a reason to inspect data lineage, trades, and timing before interpreting performance." ] } ], "faq": [ { "question": "What is a simple example of look-ahead bias?", "answer": "Using a daily closing price to generate a signal and filling the resulting order at that same close, without an intrabar auction or execution model, uses information before it was fully available." }, { "question": "Are adjusted prices always wrong for backtesting?", "answer": "No. Adjusted data can support return and indicator calculations, but normalization must match the strategy question. Problems arise when adjusted values reveal later corporate actions, conflict with live handling, or duplicate separately modeled dividends and splits." }, { "question": "How does survivorship bias differ from look-ahead bias?", "answer": "Survivorship bias excludes assets that disappeared before today. It becomes look-ahead bias when today's survivors or index members define choices available to a strategy in the past." }, { "question": "Can an event-driven backtester eliminate look-ahead bias?", "answer": "No. A time frontier limits future access from correctly timestamped data, but custom datasets, revised values, current universes, preprocessing, and incorrect timestamps can still leak future information." } ], "relatedLinks": [ { "label": "Complete AI strategy backtesting guide", "url": "/guides/backtesting-ai-trading-strategies" }, { "label": "Avoid strategy overfitting", "url": "/guides/avoid-overfitting-trading-strategies" }, { "label": "Use walk-forward testing", "url": "/guides/walk-forward-testing-trading-strategies" }, { "label": "Model slippage, fees, and market impact", "url": "/guides/modeling-slippage-fees-and-market-impact" } ], "sources": [ { "label": "QuantConnect research guide: look-ahead and survivorship bias", "url": "https://www.quantconnect.com/docs/v2/writing-algorithms/key-concepts/research-guide" }, { "label": "QuantConnect live and backtest reconciliation", "url": "https://www.quantconnect.com/docs/v2/writing-algorithms/live-trading/reconciliation" }, { "label": "QuantConnect event-handler timing and corporate actions", "url": "https://www.quantconnect.com/docs/v2/writing-algorithms/key-concepts/event-handlers" }, { "label": "SEC EDGAR timestamp definitions", "url": "https://www.sec.gov/about/webmaster-frequently-asked-questions" }, { "label": "SEC EDGAR data APIs", "url": "https://www.sec.gov/search-filings/edgar-application-programming-interfaces" }, { "label": "Alpaca market-data timestamp semantics", "url": "https://docs.alpaca.markets/docs/market-data-faq" }, { "label": "Alpaca historical-bar adjustment options", "url": "https://docs.alpaca.markets/reference/stockbars" }, { "label": "scikit-learn data-leakage guidance", "url": "https://scikit-learn.org/stable/common_pitfalls.html" }, { "label": "Lumibot backtesting documentation", "url": "https://lumibot.lumiwealth.com/backtesting.html" } ], "verifiedAt": "2026-08-14" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides/modeling-slippage-fees-and-market-impact", "url": "https://botspot.trade/guides/modeling-slippage-fees-and-market-impact", "title": "Model Slippage, Fees, and Market Impact | BotSpot", "description": "Learn how to model commissions, bid-ask spreads, slippage, fill timing, liquidity, partial fills, and market impact without inventing universal assumptions.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-14", "content": { "eyebrow": "Backtesting execution-cost guide", "heading": "Model slippage, fees, and market impact without making a backtest look safer than it is", "summary": "Separate explicit fees from spread and execution effects, define when and how orders fill, scale assumptions to liquidity and order size, then test whether strategy conclusions survive less favorable execution.", "primaryAction": { "label": "Backtest a strategy in BotSpot", "url": "/ai-agent" }, "secondaryAction": { "label": "Read the backtesting guide", "url": "/guides/backtesting-ai-trading-strategies" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "1. Build an execution-cost ledger before running the backtest", "paragraphs": [ "List every cost and fill assumption separately before inspecting performance. A single generic transaction-cost number can hide double counting, missing costs, or unrealistic execution.", "Keep explicit charges, spread, price movement, and market impact identifiable even if the backtesting engine combines some of them into one fill price." ], "bullets": [ "Broker commissions, minimum charges, and volume tiers.", "Exchange, clearing, regulatory, contract, and asset-specific fees where applicable.", "Bid-ask spread paid when an order takes available liquidity.", "Price movement between the strategy decision, order submission, and fill.", "Liquidity limits, partial fills, queue behavior, and market impact." ] }, { "heading": "2. Model commissions from the intended broker workflow", "paragraphs": [ "Use the current official fee schedule for the intended broker, account type, market, asset, order, and volume tier. Do not copy a fee from a different broker or assume commission-free means cost-free.", "Represent each fee in the form it is charged: per order, per share, per contract, percentage of value, minimum charge, or tiered rate. LumiBot supports flat, percentage, and per-contract trading-fee inputs for backtests." ], "bullets": [ "Record source URL and verification date.", "Apply buy-side and sell-side charges where required.", "Include minimums and tier thresholds instead of averaging them away.", "Recheck volatile fee schedules before publishing or rerunning material analysis." ] }, { "heading": "3. Keep spread and slippage definitions consistent", "paragraphs": [ "A marketable buy generally executes against the ask and a marketable sell against the bid. A fill model using bid and ask quotes can therefore include spread directly in simulated fill prices.", "Slippage describes a difference between a declared reference price and the simulated or actual fill. State whether the reference is decision price, quote midpoint, arrival price, last trade, bar close, or another observable value." ], "bullets": [ "Do not subtract a separate spread charge when the fill model already buys at ask and sells at bid.", "Do not treat a bar close as both decision price and guaranteed fill unless timing makes that possible.", "Use quote data when available; document any bar-based spread proxy when it is not.", "Keep favorable price improvement possible only when the selected model and evidence support it." ] }, { "heading": "4. Make fill timing and order behavior feasible", "paragraphs": [ "Define when the strategy observes data, when it submits an order, which market session applies, and which later observation can first produce a fill. Same-bar fills can use information unavailable when the order would have been placed.", "Order type changes the simulation. Market orders favor execution certainty but can slip. Limit orders constrain price but may remain unfilled. Stops become eligible only after their trigger conditions occur." ], "bullets": [ "Match data resolution to decision and execution timing.", "Reject fills based on stale prices or closed-market data.", "Model unfilled, canceled, expired, and rejected orders where relevant.", "Preserve pending orders across bars instead of silently converting them into fills." ] }, { "heading": "5. Treat liquidity and partial fills as strategy inputs", "paragraphs": [ "Historical price bars do not guarantee that the full strategy order could trade at one displayed price. Available quantity, order-book depth, queue position, and competing orders affect both fill quantity and timing.", "Set liquidity rules from data and intended trade size rather than one universal volume percentage. Test what happens when only part of an order fills and the remainder stays open, reprices, expires, or is canceled." ], "bullets": [ "Compare order size with relevant traded volume and available depth.", "Prevent a simulated fill from consuming unlimited quantity at one price.", "Update cash, positions, exits, and risk rules after each partial fill.", "Check whether delayed completion changes later signals or creates overlapping orders." ] }, { "heading": "6. Scale market impact to size, liquidity, volatility, and time", "paragraphs": [ "Market impact is the price response associated with consuming liquidity and revealing demand or supply. Its size depends on factors including order size, trading volume, depth, volatility, and execution duration.", "A bar-only backtest cannot observe the order book the hypothetical trade would have consumed. Any impact result remains a model estimate. Declare model form, inputs, calibration period, and unsupported markets." ], "bullets": [ "Avoid one fixed market-impact value across symbols and order sizes.", "Increase scrutiny when orders represent a larger share of available liquidity.", "Distinguish temporary execution effects from persistent price movement when the model does.", "Recalibrate external model defaults before relying on them in a different market or period." ] }, { "heading": "7. Run sensitivity tests instead of choosing one convenient cost", "paragraphs": [ "Test a documented base case plus less favorable execution cases. Derive ranges from current fee schedules, historical quotes, intended participation, and observed execution rather than publishing universal defaults.", "Report gross results, net results, turnover, total modeled costs, and the cost level at which the strategy conclusion changes. A strategy surviving only its most optimistic fill model needs more evidence." ], "bullets": [ "Widen spreads using observed distributions for relevant symbols and sessions.", "Delay fills and reduce eligible fill quantity.", "Raise explicit costs according to plausible account or volume tiers.", "Stress high-volatility, low-liquidity, and extended-hours periods separately.", "Change one assumption at a time, then test combined adverse conditions." ] }, { "heading": "8. Compare models with observed execution carefully", "paragraphs": [ "Paper trading can validate order construction, scheduling, state, and broker integration, but its fills remain simulated. Alpaca documents that its paper environment omits market impact, latency slippage, queue position, price improvement, and regulatory fees.", "Where controlled live observations exist, compare decision timestamp, reference quote, submit time, acknowledgments, partial fills, final fill, explicit fees, order size, and market conditions. Historical observations can inform calibration but cannot guarantee future execution." ] }, { "heading": "Limitations and risk", "paragraphs": [ "No execution model reproduces every venue, queue, counterparty, outage, rejection, or future liquidity condition. More detailed assumptions reduce known simplifications; they do not turn simulated results into expected returns.", "Broker fees, market structure, data coverage, and backtesting-engine defaults can change. Preserve configuration, sources, dates, and raw trade records so results can be audited and rerun." ] } ], "faq": [ { "question": "What trading costs should a backtest include?", "answer": "Include applicable broker, exchange, clearing, regulatory, and contract fees plus bid-ask spread, slippage, fill timing, liquidity limits, partial fills, and market impact. Financing, borrow, conversion, and product costs may also matter for some strategies." }, { "question": "What slippage value should I use?", "answer": "No universal value fits every strategy. Derive assumptions from intended order type, asset, session, quote data, volatility, liquidity, order size, latency, and observed execution. Test multiple documented cases." }, { "question": "Does commission-free trading remove transaction costs?", "answer": "No. Spread, price movement, market impact, regulatory or product fees, financing, and missed or partial fills can remain even when the broker charges no stated commission." }, { "question": "Can paper trading estimate live slippage accurately?", "answer": "Not by itself. Paper systems use simulated fill and liquidity rules and may omit market impact, queue position, latency effects, fees, or price improvement. Use paper trading mainly for operational validation and document its fill assumptions." }, { "question": "How should a backtest handle partial fills?", "answer": "Fill only eligible quantity under the declared liquidity model, update portfolio state after each fill, and keep the remainder pending, canceled, or expired according to the order rules. Do not assume every order completes immediately." } ], "relatedLinks": [ { "label": "Backtest AI trading strategies", "url": "/guides/backtesting-ai-trading-strategies" }, { "label": "Understand backtesting metrics", "url": "/guides/backtesting-metrics-explained" }, { "label": "Compare paper and live trading", "url": "/guides/paper-trading-vs-live-trading" }, { "label": "Avoid overfitting trading strategies", "url": "/guides/avoid-overfitting-trading-strategies" } ], "sources": [ { "label": "LumiBot trading-fee configuration", "url": "https://lumibot.lumiwealth.com/getting_started.html" }, { "label": "QuantConnect trade fill models", "url": "https://www.quantconnect.com/docs/v2/writing-algorithms/reality-modeling/trade-fills/key-concepts" }, { "label": "QuantConnect slippage models", "url": "https://www.quantconnect.com/docs/v2/writing-algorithms/reality-modeling/slippage/supported-models" }, { "label": "QuantConnect transaction-fee models", "url": "https://www.quantconnect.com/docs/v2/writing-algorithms/reality-modeling/transaction-fees/supported-models" }, { "label": "Alpaca paper trading assumptions", "url": "https://docs.alpaca.markets/us/v1.4.2/docs/paper-trading" }, { "label": "Alpaca order behavior", "url": "https://docs.alpaca.markets/us/docs/orders-at-alpaca" }, { "label": "Investor.gov fee bulletin", "url": "https://www.investor.gov/introduction-investing/general-resources/news-alerts/alerts-bulletins/investor-bulletins/updated" }, { "label": "Investor.gov bid-ask spread explanation", "url": "https://www.investor.gov/introduction-investing/general-resources/news-alerts/alerts-bulletins/investor-bulletins-24" } ], "verifiedAt": "2026-08-14" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides/algorithmic-trading-risk-management", "url": "https://botspot.trade/guides/algorithmic-trading-risk-management", "title": "Algorithmic Trading Risk Management | BotSpot Guide", "description": "Design algorithmic trading controls for position sizing, exposure, leverage, order limits, drawdowns, monitoring, broker constraints, and emergency stops.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-14", "content": { "eyebrow": "Automated trading risk-control guide", "heading": "Build algorithmic trading risk controls around every order and failure state", "summary": "Define limits before deployment, reject orders that violate them, monitor broker state continuously, and make stopping and recovery explicit parts of the strategy design.", "primaryAction": { "label": "Build a strategy in BotSpot", "url": "/ai-agent" }, "secondaryAction": { "label": "View supported broker modes", "url": "/brokers" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "1. Separate strategy, portfolio, and operational risk", "paragraphs": [ "One exit rule cannot control every failure. Strategy risk covers how much one idea may lose. Portfolio risk covers combined positions, correlations, leverage, and concentration. Operational risk covers incorrect data, duplicate orders, rejected orders, disconnects, stale state, and software defects.", "Write limits at each layer before deployment. Broker and exchange protections remain valuable backstops, but they do not replace controls inside the strategy." ], "bullets": [ "Strategy limits: order size, position size, loss budget, and permitted instruments.", "Portfolio limits: gross exposure, net exposure, concentration, and combined working orders.", "Operational limits: message rate, data freshness, order duplication, connection health, and account-state agreement.", "Broker constraints: buying power, margin, permissions, order types, sessions, and product eligibility." ] }, { "heading": "2. Size positions from declared risk, not a universal percentage", "paragraphs": [ "No single position-size percentage fits every strategy or account. Define a maximum order quantity or notional value, maximum position exposure, and maximum combined exposure using documented capital and tested strategy behavior.", "Include existing positions and working orders when calculating exposure. Otherwise, several pending fills can individually pass a check while jointly breaching the intended limit." ], "bullets": [ "Cap exposure by symbol, strategy, asset class, sector, and account where relevant.", "Measure gross exposure as well as net exposure; offsetting directions can hide large total positions.", "Account for correlated positions rather than assuming different symbols create independent risk.", "Model gaps, slippage, fees, and partial fills instead of treating a stop price as a guaranteed loss boundary." ] }, { "heading": "3. Treat leverage and buying power as constraints, not targets", "paragraphs": [ "Broker-reported buying power describes what an account may currently submit. It does not define a prudent strategy allocation. Margin can magnify losses, create maintenance calls, and allow broker liquidation under changing house requirements.", "Read current account state before opening risk, reserve capacity for adverse movement and working orders, and stop submitting new exposure when margin or buying-power data is missing or stale." ], "bullets": [ "Use broker-reported buying power and margin fields rather than reconstructing them from old balances.", "Expect product, jurisdiction, session, and account-type rules to differ.", "Handle increased margin requirements and reduced buying power without repeatedly retrying rejected orders.", "Do not assume paper-account leverage or fills reproduce live-account behavior." ] }, { "heading": "4. Reject unsafe orders before submission", "paragraphs": [ "Pre-trade controls should block an order before it reaches the broker when required data is unavailable or a declared limit would be exceeded. Sending an unsafe order and attempting to cancel it afterward still leaves execution risk.", "Apply controls to every order path, including retries, replacements, exits, scheduled actions, and manually triggered strategy operations." ], "bullets": [ "Maximum quantity and maximum notional value per order.", "Maximum resulting position, gross exposure, net exposure, and working-order exposure.", "Price-deviation checks against fresh, appropriate market data.", "Allowed symbols, asset classes, order types, sessions, and time-in-force values.", "Buying-power, margin, shortability, and account-permission checks.", "Duplicate-order protection using stable client order identifiers.", "Order-rate and message-rate limits that stop loops and retry storms." ] }, { "heading": "5. Define loss and drawdown controls as state transitions", "paragraphs": [ "Daily-loss and peak-to-trough drawdown controls need an explicit data source, calculation method, threshold, action, and reset process. A threshold cannot protect an account when equity, realized profit and loss, or open-position values are stale.", "When a loss control triggers, block new risk first, identify outstanding orders, reconcile positions, notify the responsible operator, and require a deliberate recovery decision. Do not silently reset a breached control because the clock changed or the process restarted." ], "bullets": [ "Document whether limits use realized loss, unrealized loss, total equity, or another defined measure.", "Decide how deposits, withdrawals, overnight gaps, and multiple strategies affect the calculation.", "Store breach state outside the process that may have failed.", "Test restart behavior so a stopped strategy cannot resume with forgotten loss state." ] }, { "heading": "6. Monitor orders, positions, data, and infrastructure", "paragraphs": [ "A submitted order is not a completed trade. Monitor acknowledgements, fills, partial fills, rejections, cancellations, expirations, and replacements. Compare internal state with broker open orders, positions, balances, and buying power.", "Streaming updates reduce delay, but reconnects and missed messages require periodic reconciliation against broker state. Missing confirmation should create an unknown state, not permission to submit another order." ], "bullets": [ "Alert on stale market data, disconnected streams, delayed strategy cycles, and failed heartbeats.", "Detect position or order differences between strategy state and broker state.", "Track repeated rejects, unexpected partial fills, abnormal order volume, and control breaches.", "Preserve timestamps, inputs, decisions, orders, broker responses, and configuration versions for investigation.", "Assign a person or process responsible for responding while live risk exists." ] }, { "heading": "7. Make the kill switch precise and recoverable", "paragraphs": [ "A kill switch should have defined scope and observable confirmation. Blocking new orders, canceling working orders, stopping strategy evaluation, and closing positions are different actions. Closing positions automatically can introduce new execution and liquidity risk.", "Design the safest supported stop sequence for each broker and market. Confirm cancellation and current positions through broker state, then keep new order entry disabled until the cause is understood and recovery checks pass." ], "bullets": [ "Provide a minimal-step way to stop one strategy and, when needed, broader account activity.", "Keep emergency controls independent from the strategy process they must stop.", "Define behavior when cancellation fails, connectivity is unavailable, or an order fills during shutdown.", "Require explicit authorization and state reconciliation before resuming." ] }, { "heading": "8. Test controls and changes before increasing exposure", "paragraphs": [ "Test risk controls independently from expected strategy behavior. Simulate stale data, extreme prices, malformed quantities, duplicate signals, partial fills, order rejection, disconnects, restarts, rate limits, and unavailable broker services.", "Keep code, configuration, tests, and control parameters versioned. Deploy material changes with limited exposure and heightened monitoring before considering broader use." ] }, { "heading": "Limitations and risk", "paragraphs": [ "Risk controls can reduce selected failure modes; they cannot guarantee a maximum loss or profitable result. Markets can gap, orders can partially fill, liquidity can disappear, brokers can reject actions, and infrastructure can fail.", "Regulatory materials cited here describe obligations or practices for regulated firms and trading venues. They provide useful control-design evidence, but this guide does not determine which legal requirements apply to a particular person, strategy, broker, or jurisdiction." ] } ], "faq": [ { "question": "Which algorithmic trading risk controls should come first?", "answer": "Start with maximum order and position exposure, allowed instruments and order types, fresh-data checks, duplicate-order protection, broker-state reconciliation, monitoring alerts, and a tested stop process. Exact thresholds depend on strategy, account, products, broker, and risk tolerance." }, { "question": "Does a stop-loss order guarantee the maximum loss?", "answer": "No. A triggered stop order may become a market order and execute away from its stop price. Gaps, volatility, liquidity, slippage, and partial fills can produce a larger loss." }, { "question": "What should an algorithmic trading kill switch do?", "answer": "Its behavior must be explicit. Common actions include blocking new orders, canceling working orders, and stopping strategy evaluation. Closing positions is a separate trading decision that can create additional execution risk." }, { "question": "Can a broker reject an order that passes strategy controls?", "answer": "Yes. Brokers apply current buying-power, margin, permission, asset, session, price, quantity, and regulatory checks. Strategy controls should treat rejection as a state to reconcile, not a signal to retry indefinitely." } ], "relatedLinks": [ { "label": "Build an AI trading bot", "url": "/guides/how-to-build-an-ai-trading-bot" }, { "label": "Backtest AI trading strategies", "url": "/guides/backtesting-ai-trading-strategies" }, { "label": "Compare paper and live trading", "url": "/guides/paper-trading-vs-live-trading" }, { "label": "Explore supported broker modes", "url": "/brokers" } ], "sources": [ { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "BotSpot Terms of Service", "url": "/terms" }, { "label": "SEC Market Access Rule FAQ", "url": "https://www.sec.gov/rules-regulations/staff-guidance/trading-markets-frequently-asked-questions/divisionsmarketregfaq-0" }, { "label": "FINRA algorithmic trading supervision guidance", "url": "https://www.finra.org/rules-guidance/notices/15-09" }, { "label": "CME Group Risk Management Tools", "url": "https://www.cmegroup.com/tools-information/webhelp/globex-credit-controls/Content/Getting-Started.html" }, { "label": "FINRA brokerage and margin account guidance", "url": "https://www.finra.org/investors/investing/investment-accounts/brokerage-accounts" }, { "label": "FINRA concentration-risk guidance", "url": "https://www.finra.org/investors/insights/concentration-risk" }, { "label": "FINRA stop-order guidance", "url": "https://www.finra.org/investors/insights/stop-orders-factors-consider-during-volatile-markets" }, { "label": "Alpaca order documentation", "url": "https://docs.alpaca.markets/us/docs/orders-at-alpaca" } ], "verifiedAt": "2026-08-14" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides/connect-chatgpt-to-your-broker", "url": "https://botspot.trade/guides/connect-chatgpt-to-your-broker", "title": "Connect ChatGPT to Your Broker | BotSpot MCP Guide", "description": "Connect ChatGPT to BotSpot through OAuth MCP, verify your supported broker and account mode, and keep every trading action behind explicit approval.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-14", "content": { "eyebrow": "ChatGPT broker connection guide", "heading": "Connect ChatGPT to your broker through BotSpot", "summary": "ChatGPT connects to BotSpot through an OAuth MCP connection. Your brokerage account remains connected and managed inside BotSpot, while ChatGPT can use permitted BotSpot tools for research, strategy work, backtests, account context, and explicitly approved trading actions.", "primaryAction": { "label": "Open ChatGPT setup", "url": "/agents#agents-client-chatgpt" }, "secondaryAction": { "label": "View supported brokers", "url": "/brokers" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "1. Understand the connection boundary", "paragraphs": [ "ChatGPT does not connect directly to your broker in this workflow. ChatGPT connects to BotSpot, and BotSpot connects separately to a supported brokerage account.", "Keep broker credentials, API keys, private keys, and passwords out of ChatGPT prompts. Use BotSpot broker settings for brokerage authentication and BotSpot OAuth for the ChatGPT connection." ] }, { "heading": "2. Connect a supported broker inside BotSpot", "paragraphs": [ "Open BotSpot Broker Connections and select the broker, authentication method, and paper or live mode supported by your account. Broker support, asset classes, authentication methods, and modes can change, so verify the current broker page before continuing.", "The current BotSpot manifest lists Alpaca, Charles Schwab, Tradier, Tradovate, Kraken, Coinbase, WEEX, Bitunix, and TopstepX. These connections do not support identical assets or account modes." ], "bullets": [ "Alpaca supports listed stock, options, and crypto workflows with paper and live modes.", "Tradier supports listed stock and options workflows. Mode availability differs between OAuth and API-key connections.", "Tradovate and TopstepX cover listed futures workflows with paper and live modes.", "Charles Schwab is listed for live stock and options workflows.", "Kraken, Coinbase, WEEX, and Bitunix are listed for live crypto workflows.", "Regional eligibility, broker permissions, market-data access, and product approval still apply." ] }, { "heading": "3. Add BotSpot to ChatGPT", "paragraphs": [ "Use ChatGPT on the web. Developer mode and custom connection availability can depend on your ChatGPT account, workspace role, and administrator policy." ], "bullets": [ "Open ChatGPT Settings and enable Developer mode under Security and login when required.", "Open ChatGPT Plugins, select the plus button, and create a new MCP connection.", "Name the connection BotSpot.", "Choose Server URL and enter https://mcp.botspot.trade/mcp.", "Create the connection and let ChatGPT discover BotSpot authentication. Do not paste a BotSpot API key into ChatGPT.", "Complete BotSpot login and consent when prompted, then review the discovered tools and confirmation behavior.", "Start a new chat and enable BotSpot from the tools menu." ] }, { "heading": "4. Validate read-only access first", "paragraphs": [ "Begin with requests that inspect data without changing broker or deployment state. Confirm that ChatGPT reaches the intended BotSpot user, brokerage connection, account, and trading mode.", "Do not infer live readiness from a successful MCP connection. MCP connectivity proves tool access, not broker permissions, strategy correctness, order eligibility, or execution quality." ], "bullets": [ "Ask BotSpot to list available strategies without changing anything.", "Request an existing backtest and inspect its assumptions.", "Ask which broker and account mode are connected.", "Confirm whether the intended asset and product are supported.", "Use paper mode first where the broker connection supports it." ] }, { "heading": "5. Keep trading actions behind explicit approval", "paragraphs": [ "When direct trading is enabled, ChatGPT can ask BotSpot to prepare a supported one-time order. BotSpot presents the action for review and explicit confirmation before submission.", "MCP-driven start, stop, update, and trade requests use action-specific authorization. BotSpot checks ownership and may require a fresh login. A recent login can reduce repeated credential prompts, but it never approves or batches actions automatically.", "Review symbol, side, quantity, order type, account, broker, and paper or live mode on the BotSpot authorization page. Reject any action that differs from your request." ] }, { "heading": "6. Use prompts with clear operating boundaries", "paragraphs": [ "Tell ChatGPT which BotSpot tool boundary applies. Separate research, strategy changes, backtesting, deployment, and trading instead of combining them into one broad instruction." ], "bullets": [ "\"Using BotSpot, show my connected broker and account mode. Do not place orders or change deployments.\"", "\"Review this strategy and its latest backtest. Identify assumptions, but do not revise or deploy it.\"", "\"Prepare an order proposal for review. Do not submit anything without the BotSpot approval page.\"", "\"Use only my paper account for this test. Stop if paper mode is unavailable.\"" ] }, { "heading": "7. Troubleshoot the connection", "bullets": [ "Missing Developer mode: check ChatGPT account access and workspace administrator policy.", "Connection failure: verify the complete https://mcp.botspot.trade/mcp URL, including the /mcp path.", "OAuth remains incomplete: remove the failed connection, add it again, and finish BotSpot login and consent.", "Tools appear stale: refresh the connection metadata or start a new ChatGPT conversation.", "Broker action is unavailable: verify the BotSpot broker connection, account mode, permissions, asset support, and authentication status." ] }, { "heading": "Security and trading risk", "paragraphs": [ "OAuth access does not make AI-generated instructions trustworthy. Prompt injection, ambiguous requests, stale context, software defects, broker restrictions, and market conditions can all produce unsafe or invalid actions.", "Never paste brokerage secrets into chat. Inspect every authorization request and monitor positions, orders, balances, and deployed strategies through the broker and BotSpot." ] } ], "faq": [ { "question": "Does ChatGPT connect directly to my broker?", "answer": "No. ChatGPT connects to BotSpot through OAuth MCP. Your supported brokerage account connects separately inside BotSpot." }, { "question": "Should I paste my BotSpot or broker API key into ChatGPT?", "answer": "No. ChatGPT uses BotSpot OAuth for this connection. Enter brokerage credentials only through the appropriate BotSpot broker connection flow." }, { "question": "Can ChatGPT place a live trade automatically?", "answer": "BotSpot supports approved one-time trading actions when direct trading is enabled. The user must review and explicitly approve the action. Automated strategy deployment is a separate reviewed workflow." }, { "question": "Which brokers can I use?", "answer": "Use the current BotSpot broker directory and public manifest. Each broker supports different assets, authentication methods, paper or live modes, regions, and account permissions." }, { "question": "Why is Developer mode missing in ChatGPT?", "answer": "OpenAI documents that Developer mode availability can depend on account access and workspace policy. A workspace administrator may need to enable the required access." } ], "relatedLinks": [ { "label": "Open ChatGPT MCP setup", "url": "/agents#agents-client-chatgpt" }, { "label": "Explore supported brokers", "url": "/brokers" }, { "label": "Build an AI trading bot", "url": "/guides/how-to-build-an-ai-trading-bot" }, { "label": "Compare paper and live trading", "url": "/guides/paper-trading-vs-live-trading" } ], "sources": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "BotSpot Terms of Service", "url": "/terms" }, { "label": "OpenAI: Connect and test an MCP plugin", "url": "https://developers.openai.com/plugins/deploy/connect-chatgpt" }, { "label": "OpenAI plugin security and privacy guidance", "url": "https://developers.openai.com/plugins/guides/security-privacy" } ], "verifiedAt": "2026-08-14" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides/connect-claude-to-your-broker", "url": "https://botspot.trade/guides/connect-claude-to-your-broker", "title": "Connect Claude to Your Broker with BotSpot | Guide", "description": "Connect Claude to BotSpot through OAuth, use supported broker context, understand trade approvals, and keep brokerage credentials out of AI prompts.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-14", "content": { "eyebrow": "Claude and broker connection guide", "heading": "Connect Claude to your broker through BotSpot", "summary": "Claude connects to BotSpot through a remote OAuth MCP connector. Your brokerage account connects separately inside BotSpot. This keeps setup, broker permissions, and high-risk action approvals in their proper boundaries.", "primaryAction": { "label": "Open BotSpot MCP setup", "url": "/agents" }, "secondaryAction": { "label": "Connect a supported broker", "url": "/account-settings/broker-connections?action=add" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "1. Understand what connects to what", "paragraphs": [ "The connection path is Claude → BotSpot MCP → your BotSpot account → a saved supported broker connection. Claude does not connect directly to the broker, and adding the Claude connector does not create or authorize a brokerage account.", "BotSpot supplies research, strategy, backtest, account-context, approval, and deployment workflows. The connected broker remains the account and execution layer. Broker products, permissions, market data, regions, fees, and order eligibility still apply." ] }, { "heading": "2. Check access before setup", "paragraphs": [ "You need a BotSpot account and access to custom connectors in Claude. Anthropic currently supports remote custom connectors across Claude plans, but organization controls differ." ], "bullets": [ "Individual users add a connector from Customize → Connectors.", "On Team and Enterprise plans, an Owner or Primary Owner must add the custom connector to the organization before members connect their own accounts.", "Connect the intended brokerage account inside BotSpot. Broker setup does not happen in Claude.", "Use a paper connection first when the selected broker and BotSpot connection support paper mode." ] }, { "heading": "3. Add BotSpot as a custom Claude connector", "paragraphs": [ "In Claude, open Customize → Connectors, select Add custom connector, name it BotSpot, and enter https://mcp.botspot.trade. This is BotSpot’s Claude-specific remote MCP host.", "Complete the BotSpot OAuth login and consent flow. Then enable BotSpot for the conversation from the plus menu under Connectors." ], "bullets": [ "Use the exact HTTPS host: https://mcp.botspot.trade.", "Authenticate through the browser OAuth flow.", "Do not paste a BotSpot API key, broker password, API secret, or private key into Claude.", "Enable only the connector tools needed for the current conversation." ] }, { "heading": "4. Connect the broker inside BotSpot", "paragraphs": [ "Open BotSpot broker connections and add the account you intend to use. Authentication methods and available paper or live modes vary by broker.", "A supported broker connection does not mean every account can use every asset, order type, option level, margin feature, or trading session. Confirm account-level permissions with the broker." ], "bullets": [ "Stocks and options: Alpaca supports paper and live modes; Charles Schwab is live-only; Tradier supports paper and live modes, with mode availability depending on authentication method.", "Futures: Tradovate and TopstepX support paper and live modes.", "Crypto: Alpaca supports paper and live modes; Kraken, Coinbase, WEEX, and Bitunix are currently live-only.", "WEEX terms restrict United States and Canada eligibility. BotSpot advises using Bitunix API credentials with withdrawals disabled." ] }, { "heading": "5. Verify context with a read-first conversation", "paragraphs": [ "Enable BotSpot in a new Claude conversation and begin with a bounded read request. Confirm that Claude can identify the correct saved account, mode, strategy, or backtest before requesting any action." ], "bullets": [ "Ask Claude to list available BotSpot broker connections and their paper or live modes.", "Name the exact saved broker account when asking for balances, positions, or orders.", "Ask Claude to summarize a selected strategy revision or backtest before changing or deploying it.", "Check timestamps and account labels before relying on returned account context." ] }, { "heading": "6. Keep Claude approval and BotSpot authorization separate", "paragraphs": [ "Claude may ask whether a connector tool can run. That permission allows Claude to invoke the BotSpot tool; it is not final authorization for a brokerage action.", "BotSpot routes supported high-risk actions through a separate authorization flow. For a one-time trade, inspect the selected broker connection, account, paper or live mode, asset, side, quantity, order type, prices, and expiration before approval. Fresh login and live-risk acceptance may also be required.", "Starting, updating, or stopping an automated strategy is a separate deployment decision. Stopping a bot does not necessarily close positions already held at the broker." ], "bullets": [ "Keep write-capable trading tools on Ask or Needs approval.", "Do not choose Allow always for a financial-action tool unless you fully understand and accept unsupervised use.", "Treat paper and live approvals as different decisions.", "Reject expired, ambiguous, unexpected, or wrong-account requests." ] }, { "heading": "7. Reduce connector and credential risk", "paragraphs": [ "Anthropic warns that custom connectors can read or modify external data according to granted permissions. Connect only to the official BotSpot host, review requested access, and inspect tool inputs and outputs.", "Anthropic also warns that Research can invoke connector tools automatically. Disable write-capable BotSpot tools before using Research with the connector." ], "bullets": [ "Never place broker credentials, private keys, recovery codes, or secrets in prompts.", "Prefer broker API credentials with the minimum required permissions and withdrawals disabled where supported.", "Disable irrelevant connector tools for each conversation.", "Watch for prompt injection in webpages, documents, and other untrusted content.", "Disconnect the connector in Claude to revoke Claude access; separately revoke BotSpot or broker credentials when those credentials may be compromised." ] }, { "heading": "8. Troubleshoot without weakening controls", "bullets": [ "Connector missing: confirm BotSpot is enabled for the current conversation and, on managed plans, that an organization owner added it.", "OAuth fails: verify the exact host, finish browser login and consent, then reconnect.", "Tools look stale after a BotSpot update: remove and re-add the connector so Claude reloads its tool manifest.", "No broker account appears: connect or reconnect it inside BotSpot, not Claude.", "An order is rejected: check broker account permissions, product eligibility, market state, buying power, and order support before changing connector permissions." ] }, { "heading": "Limitations and risk", "paragraphs": [ "Claude can help inspect information and operate supported BotSpot workflows, but it cannot guarantee correct analysis, safe code, successful execution, or profitable results. AI output, backtests, paper fills, and broker data can be incomplete, delayed, or wrong.", "Review every material decision. Live trading remains exposed to market movement, latency, slippage, partial fills, fees, liquidity, outages, software defects, and broker restrictions." ] }, { "heading": "Practice this workflow live", "paragraphs": [ "Want help turning your Claude and broker connection into a repeatable research and trading workflow? Learn with Rob Grzesik in the live AI Trading Bootcamp. Review the course syllabus and decide whether the live format fits your goals." ], "links": [ { "label": "Explore the AI Trading Course & Live Bootcamp", "url": "/courses/ai-trading-bootcamp" } ] } ], "faq": [ { "question": "Does Claude connect directly to my broker?", "answer": "No. Claude connects to BotSpot through remote MCP. Your brokerage account connects separately to BotSpot through a supported broker connection." }, { "question": "Do I need a BotSpot API key for Claude?", "answer": "Not for the Claude app or Claude web custom connector. That setup uses BotSpot OAuth. Claude Code is a separate client with a separate documented setup path." }, { "question": "Which brokers can Claude use through BotSpot?", "answer": "Current BotSpot connections include Alpaca, Charles Schwab, Tradier, Tradovate, Kraken, Coinbase, WEEX, Bitunix, and TopstepX. Assets, paper or live modes, authentication, regions, and account permissions vary. Check the current broker manifest before acting." }, { "question": "Can Claude place a broker trade without my review?", "answer": "When direct trading is enabled, Claude can ask BotSpot to prepare a supported trade request. BotSpot requires a separate explicit authorization for the one-time high-risk action. Automated strategy deployment uses its own approval and operating workflow." }, { "question": "Should I give Claude my broker API key?", "answer": "No. Configure broker credentials inside BotSpot’s protected broker-connection workflow. Do not paste broker secrets or private keys into Claude." }, { "question": "Why can Claude see BotSpot but not my brokerage account?", "answer": "The Claude connector and broker connection are separate. Confirm the broker is saved and healthy in BotSpot, then name the intended saved account in the request." } ], "relatedLinks": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "View supported brokers", "url": "/brokers" }, { "label": "Connect a broker in BotSpot", "url": "/account-settings/broker-connections?action=add" }, { "label": "Compare paper and live trading", "url": "/guides/paper-trading-vs-live-trading" }, { "label": "Build an AI trading bot", "url": "/guides/how-to-build-an-ai-trading-bot" } ], "sources": [ { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "BotSpot Terms of Service", "url": "/terms" }, { "label": "Anthropic custom remote connector guide", "url": "https://support.claude.com/en/articles/11175166-get-started-with-custom-connectors-using-remote-mcp" }, { "label": "Anthropic connector guide", "url": "https://support.claude.com/en/articles/11176164-use-connectors-to-extend-claude-s-capabilities" }, { "label": "Anthropic tool-access guide", "url": "https://support.claude.com/en/articles/13730515-manage-claude-s-tool-access" } ], "verifiedAt": "2026-08-14" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/guides/connect-codex-to-your-broker", "url": "https://botspot.trade/guides/connect-codex-to-your-broker", "title": "Connect Codex to Your Broker with BotSpot | MCP Guide", "description": "Configure BotSpot MCP in Codex, keep broker credentials inside BotSpot, inspect trading context, and stage broker orders behind explicit approval.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-14", "content": { "eyebrow": "Codex MCP broker guide", "heading": "Connect Codex to your broker through BotSpot", "summary": "Codex connects to BotSpot's remote MCP server, not directly to a brokerage account. BotSpot keeps the saved broker connection, exposes permitted research and trading tools, and requires separate approval before a staged order can execute.", "primaryAction": { "label": "Create a BotSpot API key", "url": "/account-settings/api-keys" }, "secondaryAction": { "label": "Open Codex MCP setup", "url": "/agents#agents-client-codex" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "1. Understand the three-layer connection", "paragraphs": [ "Codex is the MCP client. BotSpot supplies the authenticated tools and workflow. A supported broker holds the account and executes eligible orders.", "Connect the brokerage account inside BotSpot first. Do not paste broker credentials into Codex, a prompt, a repository, or config.toml." ], "bullets": [ "Codex to BotSpot: Streamable HTTP MCP.", "Codex authentication: BotSpot API key sent as a bearer token.", "BotSpot to broker: saved BotSpot broker connection.", "Execution: subject to BotSpot approval, broker support, account permissions, and order eligibility." ] }, { "heading": "2. Create a BotSpot key and configure Codex", "paragraphs": [ "Create a BotSpot API key from Account Settings, store it in the BOTSPOT_API_KEY environment variable, then add the BotSpot server to Codex configuration.", "Use ~/.codex/config.toml for this host or .codex/config.toml inside a trusted project. Never commit the API key or write its value directly into the TOML file." ], "bullets": [ "[mcp_servers.botspot]", "url = \"https://mcp.botspot.trade/mcp\"", "bearer_token_env_var = \"BOTSPOT_API_KEY\"" ] }, { "heading": "3. Verify with a read-only request", "paragraphs": [ "Restart the Codex client after changing MCP configuration. Run codex mcp list from the CLI or use /mcp inside Codex to confirm BotSpot is connected.", "Start with a narrow prompt such as: “List my BotSpot strategies and latest backtests. Do not create, edit, deploy, or trade.” Verify returned account context before allowing write-capable work." ], "bullets": [ "A 401 response usually means the BotSpot API key was not loaded, expired, or was revoked.", "If BotSpot is missing, confirm the full endpoint ends with /mcp.", "If tool definitions changed, restart Codex so it reloads the MCP catalog." ] }, { "heading": "4. Add a conservative Codex approval policy", "paragraphs": [ "OpenAI documents per-server tool approval controls. Add default_tools_approval_mode = \"writes\" under the BotSpot MCP server when you want Codex to prompt before tools not marked read-only.", "Codex approval does not replace BotSpot trade approval. It adds a client-side checkpoint before BotSpot creates the pending action." ], "bullets": [ "default_tools_approval_mode = \"writes\"", "Use enabled_tools or disabled_tools only when you intentionally want a narrower tool surface.", "Do not configure blanket approval for write-capable trading tools." ] }, { "heading": "5. Connect a supported broker inside BotSpot", "paragraphs": [ "Current BotSpot support includes stock, options, futures, and crypto connections. Support means BotSpot can connect to the listed provider; it does not prove that every account can place every order." ], "bullets": [ "Stocks and options: Alpaca, Charles Schwab, and Tradier.", "Futures: Tradovate and TopstepX.", "Crypto: Alpaca, Kraken, Coinbase, WEEX, and Bitunix.", "Paper mode is available only for listed broker and authentication combinations.", "Broker permissions, market data, regions, fees, products, and order types remain account- and broker-specific." ] }, { "heading": "6. Stage a trade without bypassing approval", "paragraphs": [ "Ask Codex for a concrete symbol, side, quantity, order type, time in force, and required prices. When the place_trade tool is available, BotSpot validates the request and creates a pending high-risk action.", "Review the short-lived BotSpot authorization page while signed in. Confirm broker, paper or live mode, symbol, quantity, order type, prices, option legs, and exits before approving.", "Do not treat creation of the approval as execution. Use BotSpot status or get_single_trade_status after approval before claiming the order was submitted, filled, rejected, or canceled." ] }, { "heading": "7. Know when direct trading is unavailable", "paragraphs": [ "Direct trading depends on the place_trade scope being present for the current BotSpot API key and MCP session. A deliberately restricted token may expose research and account tools without exposing trade creation.", "Broker adapters can also reject unsupported order classes, account permissions, time-in-force values, or product combinations. BotSpot reports those failures without returning broker secrets." ] }, { "heading": "Safe starter prompts", "bullets": [ "“List my supported BotSpot broker connections and identify paper versus live mode. Do not change anything.”", "“Show my latest completed backtests and summarize their assumptions. Do not start a new backtest.”", "“Prepare a one-share market buy of SPY using an eligible paper connection. Stage it for BotSpot approval; do not claim it executed.”", "“Check the status of the pending trade action. Report only confirmed approval and broker status.”" ] }, { "heading": "Limitations and risk", "paragraphs": [ "MCP configuration proves connectivity, not trading readiness. Generated analysis can be wrong, backtests remain simulations, and broker execution can differ because of prices, fills, latency, liquidity, fees, permissions, outages, and changing market conditions.", "Start with read-only inspection and paper mode where supported. Review every credential scope, order payload, approval screen, and status result." ] } ], "faq": [ { "question": "Does Codex connect directly to my broker?", "answer": "No. Codex connects to BotSpot through MCP. BotSpot uses your saved supported broker connection for eligible account and execution workflows." }, { "question": "Can Codex see my broker API secret or password?", "answer": "BotSpot's MCP contract does not return raw broker secrets. Keep broker credentials inside BotSpot and keep the BotSpot API key outside prompts and committed files." }, { "question": "Can Codex place a trade without approval?", "answer": "No. BotSpot place_trade creates a pending approval request. The exact order must be reviewed and approved through BotSpot before broker submission." }, { "question": "Why is the trade tool missing?", "answer": "The current BotSpot token or session may not include the place_trade scope. Research and read-only tools can remain available under a narrower access policy." }, { "question": "Does a supported broker guarantee my order will work?", "answer": "No. Account permissions, asset eligibility, paper or live mode, market data, regional access, order types, and broker rules still apply." } ], "relatedLinks": [ { "label": "MCP for Agents", "url": "/agents" }, { "label": "View supported brokers", "url": "/brokers" }, { "label": "Compare paper and live trading", "url": "/guides/paper-trading-vs-live-trading" }, { "label": "Build an AI trading bot", "url": "/guides/how-to-build-an-ai-trading-bot" } ], "sources": [ { "label": "Official OpenAI Codex MCP documentation", "url": "https://learn.chatgpt.com/docs/extend/mcp?surface=cli" }, { "label": "BotSpot MCP for Agents", "url": "/agents" }, { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "BotSpot supported brokers", "url": "/brokers" }, { "label": "BotSpot platform comparison", "url": "/compare" }, { "label": "BotSpot Terms of Service", "url": "/terms" } ], "verifiedAt": "2026-08-14" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/brokers", "url": "https://botspot.trade/brokers", "title": "BotSpot Broker Connections | AI Trading with Your Broker", "description": "Explore supported BotSpot broker connections for stocks, options, futures, and crypto, with AI research, approved trades, and strategy automation.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "Supported broker connections", "heading": "Bring BotSpot’s AI agent to your broker", "summary": "Your broker holds the account and executes eligible orders. BotSpot supplies the conversational research, explicit approval workflow, strategy building, backtesting, and operations layer.", "primaryAction": { "label": "Connect a broker", "url": "/account-settings/broker-connections?action=add" }, "secondaryAction": { "label": "See MCP setup", "url": "/agents" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "One AI workflow across supported accounts", "paragraphs": [ "Choose a broker page to see current asset classes, paper or live modes, authentication methods, and broker-specific notices. These pages are generated from the same source used by the BotSpot connection interface and public manifest." ] } ], "cards": [ { "eyebrow": "Stocks • Options • Crypto", "heading": "Use BotSpot with Alpaca", "summary": "paper trading and live trading through OAuth and API key.", "url": "/brokers/alpaca" }, { "eyebrow": "Stocks • Options", "heading": "Use BotSpot with Charles Schwab", "summary": "live trading through OAuth.", "url": "/brokers/schwab" }, { "eyebrow": "Stocks • Options", "heading": "Use BotSpot with Tradier", "summary": "paper trading and live trading through OAuth and API key.", "url": "/brokers/tradier" }, { "eyebrow": "Futures", "heading": "Use BotSpot with Tradovate", "summary": "paper trading and live trading through API key.", "url": "/brokers/tradovate" }, { "eyebrow": "Crypto", "heading": "Use BotSpot with Kraken", "summary": "live trading through API key.", "url": "/brokers/kraken" }, { "eyebrow": "Crypto", "heading": "Use BotSpot with Coinbase", "summary": "live trading through API key.", "url": "/brokers/coinbase" }, { "eyebrow": "Crypto", "heading": "Use BotSpot with WEEX", "summary": "live trading through API key. WEEX terms restrict US and Canada eligibility.", "url": "/brokers/weex" }, { "eyebrow": "Crypto", "heading": "Use BotSpot with Bitunix", "summary": "live trading through API key. Use a scoped API key with withdrawals disabled.", "url": "/brokers/bitunix" }, { "eyebrow": "Futures", "heading": "Use BotSpot with TopstepX", "summary": "paper trading and live trading through API key.", "url": "/brokers/projectx-topstepx" } ], "relatedLinks": [ { "label": "MCP for Agents", "url": "/agents" }, { "label": "Compare BotSpot and QuantConnect", "url": "/compare/botspot-vs-quantconnect" }, { "label": "Read the platform buyer guide", "url": "/guides/automated-trading-platforms" } ], "sources": [ { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/brokers/alpaca", "url": "https://botspot.trade/brokers/alpaca", "title": "Use BotSpot with Alpaca | AI Trading Broker Connection", "description": "Connect Alpaca to BotSpot for AI research, supported approved trading actions, strategy building, backtesting, and stocks, options, and crypto workflows.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "Supported BotSpot broker connection", "heading": "Use BotSpot with Alpaca", "summary": "Connect Alpaca to the BotSpot AI trading workspace for conversational research, supported user-approved trading actions, and complete automated strategy workflows across Stocks, Options, and Crypto.", "primaryAction": { "label": "Connect Alpaca", "url": "/account-settings/broker-connections?action=add&broker=alpaca" }, "secondaryAction": { "label": "Explore every supported broker", "url": "/brokers" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "What BotSpot adds to Alpaca", "paragraphs": [ "Alpaca supplies the connected account and eligible order execution. BotSpot adds the conversational agent, research workflow, explicit trade approvals, strategy code, backtests, revisions, and operations layer." ], "bullets": [ "Research an idea before choosing whether to trade it directly or automate it.", "Prepare a one-time order for review and approval when the connected account, asset, and BotSpot action support it.", "Build, revise, backtest, and operate a complete Lumibot algorithm.", "Use BotSpot directly or work through compatible clients such as ChatGPT, Claude, Cursor, and Codex." ] }, { "heading": "Alpaca connection details", "paragraphs": [ "Current BotSpot connection data lists Stocks, Options, and Crypto with paper trading and live trading. Available connection methods are OAuth and API key.", "Broker products, permissions, market data, fees, regional eligibility, and order support can change. Confirm current requirements with the broker before connecting or trading." ] }, { "heading": "Trading safety", "paragraphs": [ "A broker connection does not authorize BotSpot to trade without your controls. One-time high-risk actions require explicit review and approval. Automated strategies require separate deployment decisions and remain exposed to market and execution risk." ] } ], "faq": [ { "question": "Can BotSpot connect to Alpaca?", "answer": "Yes. Alpaca is listed in the current BotSpot public broker connection source. Current BotSpot modes are paper trading and live trading." }, { "question": "What can the BotSpot agent do with Alpaca?", "answer": "The agent can research, help prepare one-time trading actions for explicit approval when direct trading is enabled, and build or operate strategy workflows. Exact capabilities depend on the connected account, asset, broker permissions, and current BotSpot tool support." } ], "relatedLinks": [ { "label": "MCP for Agents", "url": "/agents" }, { "label": "View every supported broker", "url": "/brokers" }, { "label": "Review BotSpot pricing", "url": "/pricing" } ], "sources": [ { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "Alpaca documentation", "url": "https://docs.alpaca.markets/us/docs/trading-api" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/brokers/schwab", "url": "https://botspot.trade/brokers/schwab", "title": "Use BotSpot with Charles Schwab | AI Trading Broker Connection", "description": "Connect Charles Schwab to BotSpot for AI research, supported approved trading actions, strategy building, backtesting, and stocks and options workflows.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "Supported BotSpot broker connection", "heading": "Use BotSpot with Charles Schwab", "summary": "Connect Charles Schwab to the BotSpot AI trading workspace for conversational research, supported user-approved trading actions, and complete automated strategy workflows across Stocks and Options.", "primaryAction": { "label": "Connect Charles Schwab", "url": "/account-settings/broker-connections?action=add&broker=schwab" }, "secondaryAction": { "label": "Explore every supported broker", "url": "/brokers" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "What BotSpot adds to Charles Schwab", "paragraphs": [ "Charles Schwab supplies the connected account and eligible order execution. BotSpot adds the conversational agent, research workflow, explicit trade approvals, strategy code, backtests, revisions, and operations layer." ], "bullets": [ "Research an idea before choosing whether to trade it directly or automate it.", "Prepare a one-time order for review and approval when the connected account, asset, and BotSpot action support it.", "Build, revise, backtest, and operate a complete Lumibot algorithm.", "Use BotSpot directly or work through compatible clients such as ChatGPT, Claude, Cursor, and Codex." ] }, { "heading": "Charles Schwab connection details", "paragraphs": [ "Current BotSpot connection data lists Stocks and Options with live trading. Available connection methods are OAuth.", "Broker products, permissions, market data, fees, regional eligibility, and order support can change. Confirm current requirements with the broker before connecting or trading." ] }, { "heading": "Trading safety", "paragraphs": [ "A broker connection does not authorize BotSpot to trade without your controls. One-time high-risk actions require explicit review and approval. Automated strategies require separate deployment decisions and remain exposed to market and execution risk." ] } ], "faq": [ { "question": "Can BotSpot connect to Charles Schwab?", "answer": "Yes. Charles Schwab is listed in the current BotSpot public broker connection source. Current BotSpot modes are live trading." }, { "question": "What can the BotSpot agent do with Charles Schwab?", "answer": "The agent can research, help prepare one-time trading actions for explicit approval when direct trading is enabled, and build or operate strategy workflows. Exact capabilities depend on the connected account, asset, broker permissions, and current BotSpot tool support." } ], "relatedLinks": [ { "label": "MCP for Agents", "url": "/agents" }, { "label": "View every supported broker", "url": "/brokers" }, { "label": "Review BotSpot pricing", "url": "/pricing" } ], "sources": [ { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "Charles Schwab documentation", "url": "https://developer.schwab.com/" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/brokers/tradier", "url": "https://botspot.trade/brokers/tradier", "title": "Use BotSpot with Tradier | AI Trading Broker Connection", "description": "Connect Tradier to BotSpot for AI research, supported approved trading actions, strategy building, backtesting, and stocks and options workflows.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "Supported BotSpot broker connection", "heading": "Use BotSpot with Tradier", "summary": "Connect Tradier to the BotSpot AI trading workspace for conversational research, supported user-approved trading actions, and complete automated strategy workflows across Stocks and Options.", "primaryAction": { "label": "Connect Tradier", "url": "/account-settings/broker-connections?action=add&broker=tradier" }, "secondaryAction": { "label": "Explore every supported broker", "url": "/brokers" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "What BotSpot adds to Tradier", "paragraphs": [ "Tradier supplies the connected account and eligible order execution. BotSpot adds the conversational agent, research workflow, explicit trade approvals, strategy code, backtests, revisions, and operations layer." ], "bullets": [ "Research an idea before choosing whether to trade it directly or automate it.", "Prepare a one-time order for review and approval when the connected account, asset, and BotSpot action support it.", "Build, revise, backtest, and operate a complete Lumibot algorithm.", "Use BotSpot directly or work through compatible clients such as ChatGPT, Claude, Cursor, and Codex." ] }, { "heading": "Tradier connection details", "paragraphs": [ "Current BotSpot connection data lists Stocks and Options with paper trading and live trading. Available connection methods are OAuth and API key.", "Broker products, permissions, market data, fees, regional eligibility, and order support can change. Confirm current requirements with the broker before connecting or trading." ] }, { "heading": "Trading safety", "paragraphs": [ "A broker connection does not authorize BotSpot to trade without your controls. One-time high-risk actions require explicit review and approval. Automated strategies require separate deployment decisions and remain exposed to market and execution risk." ] } ], "faq": [ { "question": "Can BotSpot connect to Tradier?", "answer": "Yes. Tradier is listed in the current BotSpot public broker connection source. Current BotSpot modes are paper trading and live trading." }, { "question": "What can the BotSpot agent do with Tradier?", "answer": "The agent can research, help prepare one-time trading actions for explicit approval when direct trading is enabled, and build or operate strategy workflows. Exact capabilities depend on the connected account, asset, broker permissions, and current BotSpot tool support." } ], "relatedLinks": [ { "label": "MCP for Agents", "url": "/agents" }, { "label": "View every supported broker", "url": "/brokers" }, { "label": "Review BotSpot pricing", "url": "/pricing" } ], "sources": [ { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "Tradier documentation", "url": "https://docs.tradier.com/docs/trading" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/brokers/tradovate", "url": "https://botspot.trade/brokers/tradovate", "title": "Use BotSpot with Tradovate | AI Trading Broker Connection", "description": "Connect Tradovate to BotSpot for AI research, supported approved trading actions, strategy building, backtesting, and futures workflows.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "Supported BotSpot broker connection", "heading": "Use BotSpot with Tradovate", "summary": "Connect Tradovate to the BotSpot AI trading workspace for conversational research, supported user-approved trading actions, and complete automated strategy workflows across Futures.", "primaryAction": { "label": "Connect Tradovate", "url": "/account-settings/broker-connections?action=add&broker=tradovate" }, "secondaryAction": { "label": "Explore every supported broker", "url": "/brokers" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "What BotSpot adds to Tradovate", "paragraphs": [ "Tradovate supplies the connected account and eligible order execution. BotSpot adds the conversational agent, research workflow, explicit trade approvals, strategy code, backtests, revisions, and operations layer." ], "bullets": [ "Research an idea before choosing whether to trade it directly or automate it.", "Prepare a one-time order for review and approval when the connected account, asset, and BotSpot action support it.", "Build, revise, backtest, and operate a complete Lumibot algorithm.", "Use BotSpot directly or work through compatible clients such as ChatGPT, Claude, Cursor, and Codex." ] }, { "heading": "Tradovate connection details", "paragraphs": [ "Current BotSpot connection data lists Futures with paper trading and live trading. Available connection methods are API key.", "Broker products, permissions, market data, fees, regional eligibility, and order support can change. Confirm current requirements with the broker before connecting or trading." ] }, { "heading": "Trading safety", "paragraphs": [ "A broker connection does not authorize BotSpot to trade without your controls. One-time high-risk actions require explicit review and approval. Automated strategies require separate deployment decisions and remain exposed to market and execution risk." ] } ], "faq": [ { "question": "Can BotSpot connect to Tradovate?", "answer": "Yes. Tradovate is listed in the current BotSpot public broker connection source. Current BotSpot modes are paper trading and live trading." }, { "question": "What can the BotSpot agent do with Tradovate?", "answer": "The agent can research, help prepare one-time trading actions for explicit approval when direct trading is enabled, and build or operate strategy workflows. Exact capabilities depend on the connected account, asset, broker permissions, and current BotSpot tool support." } ], "relatedLinks": [ { "label": "MCP for Agents", "url": "/agents" }, { "label": "View every supported broker", "url": "/brokers" }, { "label": "Review BotSpot pricing", "url": "/pricing" } ], "sources": [ { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "Tradovate documentation", "url": "https://api-d.tradovate.com/" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/brokers/kraken", "url": "https://botspot.trade/brokers/kraken", "title": "Use BotSpot with Kraken | AI Trading Broker Connection", "description": "Connect Kraken to BotSpot for AI research, supported approved trading actions, strategy building, backtesting, and crypto workflows.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "Supported BotSpot broker connection", "heading": "Use BotSpot with Kraken", "summary": "Connect Kraken to the BotSpot AI trading workspace for conversational research, supported user-approved trading actions, and complete automated strategy workflows across Crypto.", "primaryAction": { "label": "Connect Kraken", "url": "/account-settings/broker-connections?action=add&broker=kraken" }, "secondaryAction": { "label": "Explore every supported broker", "url": "/brokers" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "What BotSpot adds to Kraken", "paragraphs": [ "Kraken supplies the connected account and eligible order execution. BotSpot adds the conversational agent, research workflow, explicit trade approvals, strategy code, backtests, revisions, and operations layer." ], "bullets": [ "Research an idea before choosing whether to trade it directly or automate it.", "Prepare a one-time order for review and approval when the connected account, asset, and BotSpot action support it.", "Build, revise, backtest, and operate a complete Lumibot algorithm.", "Use BotSpot directly or work through compatible clients such as ChatGPT, Claude, Cursor, and Codex." ] }, { "heading": "Kraken connection details", "paragraphs": [ "Current BotSpot connection data lists Crypto with live trading. Available connection methods are API key.", "Broker products, permissions, market data, fees, regional eligibility, and order support can change. Confirm current requirements with the broker before connecting or trading." ] }, { "heading": "Trading safety", "paragraphs": [ "A broker connection does not authorize BotSpot to trade without your controls. One-time high-risk actions require explicit review and approval. Automated strategies require separate deployment decisions and remain exposed to market and execution risk." ] } ], "faq": [ { "question": "Can BotSpot connect to Kraken?", "answer": "Yes. Kraken is listed in the current BotSpot public broker connection source. Current BotSpot modes are live trading." }, { "question": "What can the BotSpot agent do with Kraken?", "answer": "The agent can research, help prepare one-time trading actions for explicit approval when direct trading is enabled, and build or operate strategy workflows. Exact capabilities depend on the connected account, asset, broker permissions, and current BotSpot tool support." } ], "relatedLinks": [ { "label": "MCP for Agents", "url": "/agents" }, { "label": "View every supported broker", "url": "/brokers" }, { "label": "Review BotSpot pricing", "url": "/pricing" } ], "sources": [ { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "Kraken documentation", "url": "https://docs.kraken.com/" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/brokers/coinbase", "url": "https://botspot.trade/brokers/coinbase", "title": "Use BotSpot with Coinbase | AI Trading Broker Connection", "description": "Connect Coinbase to BotSpot for AI research, supported approved trading actions, strategy building, backtesting, and crypto workflows.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "Supported BotSpot broker connection", "heading": "Use BotSpot with Coinbase", "summary": "Connect Coinbase to the BotSpot AI trading workspace for conversational research, supported user-approved trading actions, and complete automated strategy workflows across Crypto.", "primaryAction": { "label": "Connect Coinbase", "url": "/account-settings/broker-connections?action=add&broker=coinbase" }, "secondaryAction": { "label": "Explore every supported broker", "url": "/brokers" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "What BotSpot adds to Coinbase", "paragraphs": [ "Coinbase supplies the connected account and eligible order execution. BotSpot adds the conversational agent, research workflow, explicit trade approvals, strategy code, backtests, revisions, and operations layer." ], "bullets": [ "Research an idea before choosing whether to trade it directly or automate it.", "Prepare a one-time order for review and approval when the connected account, asset, and BotSpot action support it.", "Build, revise, backtest, and operate a complete Lumibot algorithm.", "Use BotSpot directly or work through compatible clients such as ChatGPT, Claude, Cursor, and Codex." ] }, { "heading": "Coinbase connection details", "paragraphs": [ "Current BotSpot connection data lists Crypto with live trading. Available connection methods are API key.", "Broker products, permissions, market data, fees, regional eligibility, and order support can change. Confirm current requirements with the broker before connecting or trading." ] }, { "heading": "Trading safety", "paragraphs": [ "A broker connection does not authorize BotSpot to trade without your controls. One-time high-risk actions require explicit review and approval. Automated strategies require separate deployment decisions and remain exposed to market and execution risk." ] } ], "faq": [ { "question": "Can BotSpot connect to Coinbase?", "answer": "Yes. Coinbase is listed in the current BotSpot public broker connection source. Current BotSpot modes are live trading." }, { "question": "What can the BotSpot agent do with Coinbase?", "answer": "The agent can research, help prepare one-time trading actions for explicit approval when direct trading is enabled, and build or operate strategy workflows. Exact capabilities depend on the connected account, asset, broker permissions, and current BotSpot tool support." } ], "relatedLinks": [ { "label": "MCP for Agents", "url": "/agents" }, { "label": "View every supported broker", "url": "/brokers" }, { "label": "Review BotSpot pricing", "url": "/pricing" } ], "sources": [ { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "Coinbase documentation", "url": "https://www.coinbase.com/developer-platform/products/advanced-trade-api" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/brokers/weex", "url": "https://botspot.trade/brokers/weex", "title": "Use BotSpot with WEEX | AI Trading Broker Connection", "description": "Connect WEEX to BotSpot for AI research, supported approved trading actions, strategy building, backtesting, and crypto workflows.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "Supported BotSpot broker connection", "heading": "Use BotSpot with WEEX", "summary": "Connect WEEX to the BotSpot AI trading workspace for conversational research, supported user-approved trading actions, and complete automated strategy workflows across Crypto.", "primaryAction": { "label": "Connect WEEX", "url": "/account-settings/broker-connections?action=add&broker=weex" }, "secondaryAction": { "label": "Explore every supported broker", "url": "/brokers" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "What BotSpot adds to WEEX", "paragraphs": [ "WEEX supplies the connected account and eligible order execution. BotSpot adds the conversational agent, research workflow, explicit trade approvals, strategy code, backtests, revisions, and operations layer." ], "bullets": [ "Research an idea before choosing whether to trade it directly or automate it.", "Prepare a one-time order for review and approval when the connected account, asset, and BotSpot action support it.", "Build, revise, backtest, and operate a complete Lumibot algorithm.", "Use BotSpot directly or work through compatible clients such as ChatGPT, Claude, Cursor, and Codex." ] }, { "heading": "WEEX connection details", "paragraphs": [ "Current BotSpot connection data lists Crypto with live trading. Available connection methods are API key.", "WEEX terms restrict US and Canada eligibility.", "Broker products, permissions, market data, fees, regional eligibility, and order support can change. Confirm current requirements with the broker before connecting or trading." ] }, { "heading": "Trading safety", "paragraphs": [ "A broker connection does not authorize BotSpot to trade without your controls. One-time high-risk actions require explicit review and approval. Automated strategies require separate deployment decisions and remain exposed to market and execution risk." ] } ], "faq": [ { "question": "Can BotSpot connect to WEEX?", "answer": "Yes. WEEX is listed in the current BotSpot public broker connection source. Current BotSpot modes are live trading." }, { "question": "What can the BotSpot agent do with WEEX?", "answer": "The agent can research, help prepare one-time trading actions for explicit approval when direct trading is enabled, and build or operate strategy workflows. Exact capabilities depend on the connected account, asset, broker permissions, and current BotSpot tool support." } ], "relatedLinks": [ { "label": "MCP for Agents", "url": "/agents" }, { "label": "View every supported broker", "url": "/brokers" }, { "label": "Review BotSpot pricing", "url": "/pricing" } ], "sources": [ { "label": "BotSpot broker connection manifest", "url": "/.well-known/botspot-manifest.json" }, { "label": "WEEX documentation", "url": "https://www.weex.com/api-doc/spot/introduction/APIBriefIntroduction" }, { "label": "Lumibot documentation", "url": "https://lumibot.lumiwealth.com/" } ], "verifiedAt": "2026-08-17" }, "authenticated": false, "sitemap": true, "llms": true, "robots": "index, follow" }, { "path": "/brokers/bitunix", "url": "https://botspot.trade/brokers/bitunix", "title": "Use BotSpot with Bitunix | AI Trading Broker Connection", "description": "Connect Bitunix to BotSpot for AI research, supported approved trading actions, strategy building, backtesting, and crypto workflows.", "image": "https://botspot.trade/social-share-image.jpg", "pageType": "article", "name": null, "startDate": null, "lastmod": "2026-08-17", "content": { "eyebrow": "Supported BotSpot broker connection", "heading": "Use BotSpot with Bitunix", "summary": "Connect Bitunix to the BotSpot AI trading workspace for conversational research, supported user-approved trading actions, and complete automated strategy workflows across Crypto.", "primaryAction": { "label": "Connect Bitunix", "url": "/account-settings/broker-connections?action=add&broker=bitunix" }, "secondaryAction": { "label": "Explore every supported broker", "url": "/brokers" }, "proofPoints": [ { "title": "Research by conversation", "text": "Ask the agent to investigate markets, companies, filings, strategies, and your connected account context." }, { "title": "Place approved direct trades", "text": "When direct trading is enabled, request a one-time trade in plain English, inspect the order, and approve it before submission." }, { "title": "Build complete algorithms", "text": "Create, revise, backtest, connect, and operate Lumibot strategies without assembling the full application stack yourself." }, { "title": "Use the AI client you prefer", "text": "Work in BotSpot or connect through ChatGPT, Claude, Cursor, Codex, and other compatible MCP clients." } ], "sections": [ { "heading": "What BotSpot adds to Bitunix", "paragraphs": [ "Bitunix supplies the connected account and eligible order execution. 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