The Quant Researcher’s Reading List

Quant researchers are usually well-read in technique and under-read in everything else. A reading list that helps you think about markets, history, model fragility and human judgement tends to be more valuable in the long run than another paper on a marginal factor variant. Here is an opinionated selection from our desk.

For thinking about risk

Mandelbrot and Hudson’s The (Mis)Behaviour of Markets remains the most accessible introduction to the limits of Gaussian intuition. Taleb’s Fooled by Randomness and Antifragile push the same idea into operational territory. For institutional readers, Bernstein’s Against the Gods is the canonical history of how we came to think we can measure uncertainty at all.

For thinking about strategy

Ang’s Asset Management is the most coherent academic treatment of factor investing for institutional readers. Pedersen’s Efficiently Inefficient is excellent on the practitioner side. For systematic trading specifically, Rob Carver’s books — Systematic Trading and Leveraged Trading — are unmatched in their honesty about what works and what does not.

For thinking about models

López de Prado’s Advances in Financial Machine Learning is the discipline’s reference text for honest ML on financial data. Hull’s Options, Futures and Other Derivatives remains the practitioner standard. For methodology, McElreath’s Statistical Rethinking is the single best book on how to actually think Bayesianly.

For thinking about institutions

Lewis’s Flash Boys and Patterson’s The Quants are flawed in places but worth reading for the operational context. Swensen’s Pioneering Portfolio Management is the canonical text on endowment investing and remains, in our view, the best one-volume education on long-horizon allocation.

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