Interdisciplinary Methods for Quantitative Finance

MET AD 587

This course expands upon the foundations of finance theory with interdisciplinary approaches from statistical physics and machine learning. The course equips the students with the Python tools to tackle a broad range of problems in quantitative financial analysis and combines the study of relevant financial concepts with computational implementations. Students will learn to use packages like Numpy, Pandas, Statsmodels and Scikit, which are commonly used in research and in the industry. Prerequisites: MET AD 685 or PY 355 or equivalent or consent by the instructor.

SPRG 2023 Schedule

Section Instructor Location Schedule Notes
A1 Becker PSY B51 M 6:00 pm-8:45 pm Prereq: AD685

Note that this information may change at any time. Please visit the Student Link for the most up-to-date course information.