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February 2022 – Headlands Technologies LLC Blog

blog.headlandstech.com · 7,665 words · saved by 1 readers

This is the first in a series of book recommendations for new quants. We will only focus on books that quants commonly come across in their journey. Elements of Statistical Learning (ESL) is the classic recommendation for new quants, for good reason. However it’s a massive tome and many sections aren’t that useful – reflecting older techniques, the authors’ personal research agendas, or things that aren’t applicable to the trading domain. Chapters 1, 2, 3, and 7 are all great, constituting one of the best foundations for building empirical models from data. The framing of the model-building problem in ESL fits the trading domain better than other common entry points into statistical learning like Bayesian learning, NLP, bandits, convergence proofs, reinforcement learning, or statistical mechanics – which all emphasize assumptions that are inapplicable to trading. Trading is essentially empirical, extracting transient patterns from recent data, neither IID nor even stationary. Trading i

This is the first in a series of book recommendations for new quants. We will only focus on books that quants commonly come across in their journey. Elements of Statistical Learning (ESL) is the classic recommendation for new quants, for good reason. However it’s a massive tome and many sections aren’t that useful – reflecting older techniques, the authors’ personal research agendas, or things that aren’t applicable to the trading domain. Chapters 1, 2, 3, and 7 are all great, constituting one of the best foundations for building empirical models from data. The fr

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