Stony Brook University 3 credits AMS
This course will merge ML and traditional quantitative finance techniques employed at investment banks, asset management, and securities trading firms. It will provide a systematic introduction to statistical learning and machine learning methods applied in Quantitative Finance. The topics discussed in the course fall broadly into four categories which (as time permits) will be discussed in this order: Probabilistic Modeling, Feedforward neural networks, Sequential Learning, and Reinforcement Learning. 3 credits Prerequisite: AMS 572 & AMS 595 (or AMS 561 or based on Python knowledge per Instructor Consent) Grading Letter graded (A, A-, B+, etc.)
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