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Agentic Quant Trading with Python
This book is 100% completeLast updated on 2026-09-13
Learn to question AI-generated trading code. Follow the data, verify backtest accounting, and understand regime models, position sizing and risk controls.
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About the Book
Build a clearer understanding of AI-assisted trading systems
A practical Python guide to data pipelines, backtest accounting, hidden Markov models, Kalman filtering, pairs trading, position sizing, reinforcement learning and system operations.
For readers comfortable with basic Python who want to understand and review quantitative trading software. Start with data and backtest chapters before regime models and reinforcement learning.
English PDF edition. Code excerpts explain the implementations discussed in the book. Access to private production repositories or complete application source code is not included.
AI was used extensively in preparing the manuscript. The author personally checked important code and validation work. Examples need to be adapted and tested in your own environment. This is educational material about software and verification; it does not guarantee live trading profitability.
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