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.
3 units · Letter or Credit/No Credit
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.
Offered in Spring 2027 at Stanford University.