Reading List

The books we recommend for building agentic AI trading agents — covering algorithmic trading, machine learning for markets, and working effectively with AI. We update the shelf as new standouts appear.

Affiliate note: book links are Amazon affiliate links. As an Amazon Associate we earn from qualifying purchases, at no extra cost to you. We only list books we genuinely rate. Educational — not financial advice.

Quant & Algorithmic Trading

Advances in Financial Machine Learning
Marcos López de Prado

The reference on applying ML to markets the right way — labelling, cross-validation that respects time, and the backtest pitfalls that sink most strategies. Dense but essential.

Machine Learning for Algorithmic Trading
Stefan Jansen

A practical, code-heavy walk from data to backtest in Python. The closest thing to a hands-on companion for the kind of agent harness we write about.

Algorithmic Trading: Winning Strategies and Their Rationale
Ernest P. Chan

A readable intro to systematic strategy design, mean reversion vs momentum, and realistic expectations for the retail quant. Good before you automate anything.

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Working with AI & Agents

Co-Intelligence: Living and Working with AI
Ethan Mollick

An accessible look at where LLMs genuinely help and where they fail — useful grounding before you trust an agent with any decision, financial or otherwise.

Mindset & Risk

Fooled by Randomness
Nassim Nicholas Taleb

A vital antidote to backtest euphoria — how easily we mistake luck for skill in markets. Read it before you believe your equity curve.

Suggest a book: read something that sharpened how you build or evaluate trading systems? Tell us — we review every suggestion.

Recommendations are editorial opinion and for education only — not financial advice. Book links may be affiliate links; see our disclosure.