About the Author

I'm a software engineer with a background in data science, machine learning, and AI. I've spent years building systems that turn raw data into actionable insights — and this book is the result of applying that same approach to the stock market.

The Problem with Trading Education

Most trading “education” follows the same pattern: bold claims, cherry-picked examples, and zero transparency about methodology. Expensive courses promise life-changing returns but never show their backtests. Discord channels share “signals” with no statistical evidence.

The barrier to entry for calling yourself a trading guru is zero. Anyone can point to a chart after the fact and claim they saw it coming.

A Different Approach

This book takes the opposite approach. Every claim is backed by data. Every strategy is backtested across 26 years of SPY history. Every result — good and bad — is documented with charts, win rates, and performance metrics.

I wrote the book I wish existed when I started exploring quantitative trading: rigorous, transparent, and focused on what the data actually shows rather than what makes a good story.

The strategies are fully spelled out so you can verify them yourself. That's the whole point — you shouldn't have to take anyone's word for it.