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Guides, listicles, how-tos, and competitor comparisons. Use historical base rates, factor matching, and the TradeOdds database to make better-informed trading decisions.
Articles
What Is a Trading Edge? The 385-Trade Math That Proves It
A trading edge is a measurable probability tilt, not a feeling. Here's the expectancy math, why a 55% win rate needs about 385 trades to prove itself, and how to check a setup against 30 years of history.
8 Best Market Data APIs for AI Stock Analysis (2026)
A vendor-neutral 2026 guide to feeding real stock data into Claude and ChatGPT, with a provider comparison, setup steps, and how to catch AI hallucinations.
The Best Month to Buy Stocks: 30 Years of S&P 500 Data
We ran 30 years of S&P 500 data to find the best and worst months to buy. The answer overturns two things almost everyone believes about October and September.
5 Ways to Connect Claude to Stock Market Data in 2026
Five practical patterns for giving Claude access to historical stock market data — MCP servers, REST APIs, file uploads, Claude Projects, and Custom GPT bundles. Pros, cons, and when to use each.
Best APIs for Trading Bots in 2026: 8 Market Data Platforms Compared
Honest comparison of the 8 market data APIs most commonly used for building trading bots in 2026. Pricing, history depth, real-time access, factor pre-computation, MCP support, and Python SDK availability — all verified on the date noted.
Best Stock Backtest Platforms in 2026: 7 Tools Compared by Power and Price
Honest comparison of 7 stock backtesting platforms in 2026. QuantConnect, Backtrader, Zipline, TradeOdds, Composer, Trality, Backtesting.py — covered by category, learning curve, deployment path, and cost. Verified June 2026.
How to Backtest a Trade Idea with Claude (Natural Language, 2026)
Use Claude Desktop with the TradeOdds MCP to backtest any trade idea in plain English. Three example prompts and what to expect.
How to Build a Custom GPT for Stock Analysis (2026 Guide)
Step-by-step guide to building a ChatGPT Custom GPT that runs real stock market analysis. Uses TradeOdds' OpenAI Actions config. 10 minute setup.
How to Connect Claude to Stock Market Data (MCP Setup, 2026)
Step-by-step guide to giving Claude Desktop access to historical stock market data via the TradeOdds MCP server. Two commands, a config snippet, a restart. 5 minutes.
How to Connect Cursor to Stock Trading Data (MCP Setup, 2026)
Give Cursor's AI access to historical stock market data via TradeOdds' MCP server. Configure once, query during any coding session. Five minute setup.
How to Pick a Data Feed for Your Trading Bot (2026 Decision Guide)
Practical decision tree for choosing a market data feed for a stock trading bot in 2026. Compare cost, latency, history depth, factor pre-computation, and AI/MCP integration.
How to Write SQL Against Historical Stock Data (Power User Tier, 2026)
Practical guide to writing SQL queries against TradeOdds' indexed 35-year stock market database. Schema walkthrough, query examples, and credit math.
Open-to-Close vs Close-to-Close Returns: Why the Difference Matters in Backtesting
Forward returns can be measured close-to-close (theoretical) or next-open-to-close (executable). Each gives a different number for the same setup. Here's why the gap matters and which to use for which job.
What is Walk-Forward Validation? (Quant Backtesting Concept Explained)
Walk-forward validation is the standard way to check whether a trading strategy actually has out-of-sample edge. This explains how it works, why it matters, and what to look for in results.
Why Pre-Computed Factor Columns Matter (For Quantitative Backtesting)
Pre-computed factor columns turn what would be a week of data engineering into a single SQL query. Here's how indexed buckets, bitmasking, and column-stored forward returns make sub-second universe scans possible.
Factor Match Explained: Scan 2,000+ Stocks by Current Market Conditions
Learn how Factor Match scans 2,000+ stocks by their current quantitative fingerprint to find assets in historically significant situations.
How to Backtest a Single Trade Against History (No Code Required)
Most backtesting tools require coded strategies. TradeOdds lets you backtest a single trade against 20 years of history in seconds.
How to Find Historical Stock Pattern Matches (Without Drawing Lines on Charts)
Learn how TradeOdds finds historical stock pattern matches using 17 quantitative conditions instead of subjective chart patterns.
Stock Win Rate Calculator: How to Check Historical Odds for Any Trade
Use TradeOdds as a stock win rate calculator. See how often similar market conditions led to positive outcomes across 20 years of data.
What Is a Stock Base Rate? Bayesian Thinking for Market Analysis
Understand stock base rates, how Bayesian reasoning applies to markets, and how TradeOdds calculates historical base rates for any trading day.
Comparisons
All comparisons →TradeOdds vs Alpha Vantage: Rate-Limited Raw Data vs Indexed Factor Database (2026)
Side-by-side comparison of TradeOdds and Alpha Vantage Premium. Pricing, request limits, history depth, factor pre-computation, SQL access, and MCP integration — verified June 2026.
TradeOdds vs Polygon.io (Massive): Raw OHLCV vs Pre-Computed Factors (2026)
Side-by-side comparison of TradeOdds and Polygon.io (now branded Massive). Pricing tiers, history depth, pre-computed factors, SQL access, MCP support — all verified June 2026.
TradeOdds vs QuantConnect: Data Layer vs Backtest Engine (2026)
Side-by-side comparison of TradeOdds and QuantConnect. Backtesting, research nodes, SQL access, pre-computed factors, MCP support, pricing — verified June 2026.
TradeOdds vs Tiingo: Cheap Raw Data vs Pre-Computed Factor Database (2026)
Side-by-side comparison of TradeOdds and Tiingo. Pricing, history depth, factor pre-computation, SQL access, and AI integrations — verified June 2026.
TradeOdds vs Prospero.ai: Transparent Base Rates vs AI Stock Picks
Compare TradeOdds and Prospero.ai. AI-driven stock recommendations vs transparent historical base rates — which approach fits your trading process?
TradeOdds vs Tickeron: Historical Records vs AI Pattern Predictions
Compare TradeOdds and Tickeron. AI-driven pattern predictions vs transparent historical base rates — two fundamentally different market analysis philosophies.
TradeOdds vs TrendSpider: Historical Base Rates vs Pattern Recognition
Compare TradeOdds and TrendSpider. Two different approaches to market analysis — quantitative condition matching vs automated chart pattern scanning.