Courses

This Ph.D. course is aimed to partially fill a knowledge gap in between financial economic theories and empirical implementations in a practical way. Through empirical case studies, essential knowledge of major financial databases, CRSP, Compustat, I/B/E/S, and Refinitive Ownership is introduced with a concise SAS execution of widely used applications, Fama and French 3 Factors, Event Studies, Post-earning Announcement Drift and DGTW adjusted returns. Students are expected to understand the empirical asset pricing issues of various research methodology and resources underlying each sub-field. [Selected Slides]

This course teaches students the hands-on skills necessary to manipulate large-scale financial databases and build empirical models. The course will cover three applications of empirical analytics in this setting: (i) Fama and French model, (ii) Event Studies, and (iii) forecasting future earnings. The course is organized as a hybrid of a traditional seminar course and a computer science course and will include theoretical introduction, team programming, and presentation. [Sample Teamwork Presentation Slides ONE and TWO]