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ICT vs. Price Action: Is Liquidity Sweep Trading a Data-Backed Edge?
A data-driven deep dive into ICT Smart Money Concepts vs. Classic Price Action using Python backtesting on BTC-USD.
Coding Al Brooks: The Mathematical Failure of the Always-In Rule in Crypto vs. Equities
What happens when you convert Al Brooks' Always-In Long and Always-In Short framework into a systematic Python engine and benchmark it across Bitcoin and the S&P 500? The data shows where the idea holds up, where it breaks down, and why market structure matters.
I Coded Al Brooks' Trading Range Detection in Python and Ran It Live on Three Markets (Dax, Dow Jones Index, and Nasdaq)
What happens when you translate Al Brooks' trading range, barbwire, and breakout rules into Python — and point them at the Nasdaq, Dow, and DAX with the same thresholds? Here's what actually worked, and what still needs work.
I Backtested the 3 Most Popular RSI Strategies. Here's the Autopsy.
RSI 70/30, RSI divergence, and RSI + 200MA — three strategies taught on thousands of blogs and YouTube channels. I ran all three on 15 years of SPY data. Two lost money. One barely broke even. Here's exactly what the numbers showed.
I Coded Al Brooks' Buy Signal Bar in Python and Tested It on 23,000 Bars
What happens when you translate Al Brooks' most-used bullish entry trigger into a strict mathematical formula and backtest it on real SPY data? The results are more nuanced than you'd expect.
Al Brooks' Trend Bars vs Trading Range Bars — Coded in Python
Before you can use any Brooks setup, you need to read individual bars correctly. Trend bars and trading range bars are the foundation — here's how to define them in code and what the data shows.