ML Reference

Supervised & Unsupervised Learning

Introduction to Machine Learning with Python by Andreas C. Muller

Hands-On Machine Learning with Scikit-Learn and TensorFlow by A. Geron

Deep Learning by I. Goodfellow, Y. Bengio, A. Courville

Pattern Recognition and Machine Learning by C. Bishop

Machine Learning: A Probabilistic Perspective by K. Murphy

A Tutorial on Support Vector Regression by A. Smola and B. Scholkopf, vol. 14, p. 199-229, 2004

“Size and book-to-market factors in earnings and returns” by E. Fama and K. French, Journal of Finance, Vol. 50, No. 1 (1995), p. 131-155

“Value investing: the use of historical financial statement information to separate winners from losers” by J. Piotroski, Journal of Accounting Research, Vol. 38 (2000), p. 1 – 41

The Business of Artificial Intelligence by HBR

How AI And Automation Will Shape Finance In The Future by Workday

Reinforcement Learning

Reinforcement Learning; An introduction by Richard S. Sutton and Andrew G. Barto

M. Potters, J.P. Bouchaud, and D. Sestovic, “Hedged Monte Carlo: low variance derivative pricing with objective probabilities”, https://arxiv.org/abs/cond-mat/0008147

1. I. Halperin, “QLBS: Q-Learner in the Black-Scholes(-Merton) Worlds”, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3087076

S. Boyd, E. Busseti, S. Diamond, R.N. Kahn, J. Koh, P. Nystrup, and J. Speth, “Multi-period trading via Convex Optimization”, https://arxiv.org/abs/1705.00109