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MET AD 587

Interdisciplinary Methods for Quantitative Finance

Prerequisite: MET AD 100 Lab. 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.

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