Resources
Guides for the research side of trading
Practical writing on backtesting, validation, and research workflow — plus a printable checklist you can run before every trade.
Backtesting Software: What to Check Before You Commit
How to evaluate backtesting software: execution realism, cost modeling, out-of-sample testing, and the path from a passing test to a paper run — with a short checklist.
Read GuideMean Reversion Screening: Finding Candidates That Revert
What a mean-reversion screen should measure — distance from a reference, liquidity, volatility state — and where screens lie: survivorship, costs, and regime blindness.
Read GuideOptions Backtesting: Why It Is Harder Than Stock Backtesting
Options backtesting adds valuation models, contract selection, and fill realism to the usual questions. The three variables that break naive tests, and what to demand instead.
Read GuideWalk-Forward Validation: Testing on Unseen Data
How walk-forward validation works step by step — window splits, bounded tuning, frozen parameters — and how to read the results without lying to yourself.
Read GuideTrading Strategy Templates: A Starting Point, Not a Shortcut
What makes a trading strategy template worth using, how to adapt one without overfitting, and the discipline that keeps template results honest.
Read GuideMulti-Asset Screening Across Equities, Options, Crypto, and Forex
Screening multiple asset classes in one process: normalize before comparing, model per-asset costs, handle session differences, and check correlation before sizing.
Read GuideBeyond the Trading Journal: When Logging Trades Isn't Enough
A trading journal records what you did but can't re-run your reasoning. The research-to-review loop that replaces the diary with executable rules.
Read GuideQuant Research Tools: Assembling a Workflow You Can Trust
Quant research fails in boring ways — data drift, look-ahead, irreproducible results. The workflow properties that matter more than the stack, and where AI honestly helps.
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