u/Conquestor0 ·
Reddit — r/algotrading
· July 21, 2026 at 15:21
· ⬆ 18 pts
· 💬 10 comments
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AI Summary
Summary
The author is an experienced quantitative trader seeking advanced (graduate/post-graduate level) books on statistics, ML, optimization, information theory, and econometrics.
No market thesis, trade idea, or investment view is presented; the post is purely a request for educational resources.
Quality assessment: Noise – no research, data, or actionable content for trading.
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I've been doing quantitative strategy development for some time now and Ive reached the point where Im struggling to find books that actually teach me something new. I already have a solid understanding of the usual topics like IS/Validation/OOS splits WFO, cross-validation, permutation tests, bootstrapping, entropy, regime detection, and the other standard robustness techniques. I recently read *Testing and Tuning Market Trading Systems* by Timothy Masters but it covered concepts I was already familiar with.
Im looking for books that are genuinely advanced and make you think differently. Perhaps graduate level or even post graduate books on statistics, machine learning, optimization, information theory, econometrics, or anything else that completely changed the way you approach research and model development. And of course it would be great if the book wasnt 10 years old. Need relevance.