Guy Gentile Introduces AI Trading Edge, a 25-Chapter Guide to Building Machine-Learning Systems for Real Markets

Companion Python code connects market-data research, feature engineering, model validation and execution in a practical quantitative workflow.

Dubai, United Arab Emirates--(Newsfile Corp. - October 9, 2026) - Guy Gentile has introduced a new research resource built around AI Trading Edge, bringing together a 25-chapter guide to machine-learning systems for financial markets and a companion Python repository that demonstrates the quantitative workflow described in the book. Written by trader and author Guy Gentile, the book covers market-data research, feature engineering, model validation, risk and execution, providing a connected framework for examining how machine-learning approaches can be developed and tested in real-market research.

Rather than treating artificial intelligence as a substitute for rigorous research, AI Trading Edge focuses on the work required to turn a trading idea into a testable system, including obtaining usable data, engineering features, separating research from evaluation, and defining risk and execution constraints.

The book connects trading concepts with practical quantitative research and programming workflows. Its progression emphasizes not simply building a model, but evaluating whether its apparent signal survives an honest out-of-sample test.

From Market Data to Model Evaluation

The material covers point-in-time data pipelines, feature engineering using order flow and market microstructure, backtesting and out-of-sample validation, reinforcement learning for execution, and LLM-based news triage. The chapters connect data quality, model design and implementation while treating validation as a central part of the research process.

Companion Python Research Repository

A companion code repository is available through GuyGentile.com. It contains Python modules covering data, features, regime analysis, models, risk and execution, alongside unit tests and synthetic fixtures. The repository provides implementation examples and testing resources that can be used as reference material for quantitative research. The code is educational research material, not a turnkey live-trading service.

Availability and Reader Resources

AI Trading Edge is available on Amazon in paperback and Kindle editions. The companion repository and additional information about the book are available through the author's website.

Amazon: https://a.co/d/0gpWIiWW

Companion code: https://guygentile.com/repository

Books and author information: https://guygentile.com/books

About Guy Gentile

Guy Gentile is a trader, author and founder of DAS Trader. AI Trading Edge is part of Gentile's broader body of work covering trading, quantitative systems, macro research and market structure. His seven-book catalog includes The Stock Operator; Bro, I'm Going Rogue; Rogue Alpha; The Rogue Code; AI Trading Edge; Liquidity Event; and The Last Human Trader. His work covers trading process, quantitative systems, macro catalysts and market structure.

Note: Educational material only. Nothing in the book or this release guarantees trading results or constitutes personalized investment advice. Trading involves risk, including loss of capital.

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