Machine Learning in Financial Mathematics




Office Location: South Hall 5508

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Project Description

Machine learning and newly developed computational tools have been applied to various fields including Probability, Statistics and Financial Mathematics. We tackle with the problems that are almost impossible to be approached ten years ago but now are available based on the improvements from theoretical development and computational power. We learn new machine learning skills, emerging ideas and apply to those problems in financial markets.   

Undergraduate Contribution

Undergraduate students are expected to learn the existing methods first, implementing them in computer codes and compute numerically important quantities. They are also encouraged to discuss their own ideas and propose new methodologies. 

Requirements and/or Application Instructions

At least one or two upper division courses completed in the Department of Statistics and Applied Probability. 
Contact the instructor directly in email.