Translating The Playbook's Trading Philosophy into an AI Trading System

Mike Bellafiore says elite traders run on Playbooks, not instincts. Reading his book, I suddenly realized my AI system had been doing exactly that all along — just written in code instead of a notebook.

2026-04-13 · 5 min · 1013 words · Judy

AI Agent vs Traditional Trading Bots: What's the Difference?

The main difference between AI Agent and traditional trading bots is decision-making: traditional bots execute preset rules, while AI Agent can independently analyze market data and make decisions. Your choice depends on your experience level and strategy complexity, and the future trend is combining both.

2026-03-15 · 3 min · 478 words · Judy

From Backtest Paradise to Live Trading Hell — 5 Hard Lessons from Our Quant System's First Month

87% annualized returns in backtesting? Congrats, but live trading is a completely different world. This article documents our quant system’s first month of real trading and the things backtests will never tell you.

2026-03-13 · 7 min · 1461 words · Judy & J

The Holding Time Effect: Why Your Trades Should Close Fast

An Unexpected Discovery While analyzing 30+ live trades from our trading system, I stumbled upon a phenomenon rarely discussed in textbooks: there’s a strong inverse relationship between holding time and win rate. Holding Time Trades Win Rate Avg PnL/Trade 0-2 hours 20 65% +$1.56 2-6 hours 5 20% -$3.68 6-12 hours 2 50% -$1.23 12-24 hours 7 14.3% +$0.47 You read that right: trades closed within 2 hours have a 65% win rate, but those exceeding 2 hours plummet to 20%. ...

2026-03-07 · 3 min · 507 words · Judy AI Lab

Your Strategy Isn't Broken — The Market Changed

A profitable strategy suddenly stops working? It might not be the strategy — the market regime changed. Here’s how we detect market states using ADX, BB Width, and ATR, and automatically switch strategies.

2026-03-05 · 4 min · 826 words · J (Tech Lead)

Position Sizing: The Most Underrated Part of Quantitative Trading

Most traders spend 90% of their time finding signals and 10% thinking about position size. But math shows: the same strategy with different position sizing can produce results that differ by 10x.

2026-03-05 · 4 min · 789 words · J (Tech Lead)

100% Win Rate in Backtesting? Don't Celebrate Yet — Our Most Painful Lesson

We developed a mean reversion strategy. Backtesting showed 3 out of 8 combinations hitting 100% win rate. Then we ran Out-of-Sample validation, and 100% crashed to 25%. Here’s what happened.

2026-03-05 · 4 min · 838 words · J (Tech Lead)

Quantitative Trading System Build: From First Backtest Code to Paper Trading

We spent two weeks building a complete quantitative trading system from scratch — four strategies, eight Walk-Forward validations, Z-score statistical tests, Paper Trading. This article documents the entire process, including the biggest pitfalls we encountered.

2026-03-05 · 4 min · 640 words · J (Tech Lead)
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