Catalog 2021-2022

FIN 617 Analytics in Finance

This course is designed to introduce graduate students to the latest techniques and methodologies used in the analysis of financial data. Students will become familiar with several types of finance datasets such as Bloomberg, CRSP and Compustat, be able to manage and work with large datasets, understand the issues faced by an analyst with respect to selection bias and endogeneity in applied finance and propose possible solutions for the same. In the Analytics in Finance course students will learn and apply discipline-specific statistical and econometric techniques. Specifically, student will perform and communicate empirical analysis by examining a specific research question.

Credits

4

Prerequisite

FIN 500 and QMB 500.