Machine Learning for Algorithmic Trading
Lecture
Main Campus
Course Description
Introduces various machine learning techniques and their practical applications in quantitative finance and algorithmic trading in three modules. The first module covers various regression methods, focusing on their role in designing pairs trading strategies and statistical arbitrage. The second module introduces the foundation of reinforcement learning, emphasizing its use in high-frequency trading. Finally, the third module explores diffusion models and generative AI, highlighting their potential in financial scenario generation and stress testing for trading strategies.
MS&E 242
Units: 3
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Typically Offered
Not Available
Grading Basis
Letter or Credit/No Credit
Class Level
Graduate
Instructional Mode
In Person
Gen Ed Requirement(s)
None
