Course Description and Overview
This course introduces students to the empirical methods used in finance, with a strong emphasis on practical application. We will explore the extensive empirical literature that analyzes movements in security prices, evaluates investment and asset pricing models, and tests these models to interpret their implications. While the course builds on the program’s econometrics sequence, the focus is on applying these techniques to real-world financial data and problems — including event studies, the analysis of short- and long-run stock returns, multi-factor models, and credit risk analysis. In addition to traditional approaches in financial econometrics, the course integrates predictive modeling techniques from data science, including applications in “Big Data” environments. Students will work with standard financial datasets and gain experience in designing, coding, and analyzing models commonly used in industry. The course structure and assignments are designed to reflect the types of tasks students are likely to encounter in professional roles in the finance industry — including positions at commercial banks, investment banks, hedge funds, mutual funds, non-banking financial institutions, central banks, consulting firms, and government agencies. Students will complete a hands-on group project involving data analysis, professional visualization of results, and in-class presentation or reporting. The goal is to equip students with the skills and experience needed to transition smoothly into applied roles in finance and related fields.
Learning Objectives
By the end of this course, students will be able to:
- Acquire foundational knowledge of empirical methods in finance;
- Be familiar with time-series and cross-sectional properties of asset returns;
- Learn how to apply modern econometric methods to important questions in finance;
- Gain experience in working with real data using python.
Prerequisite(s)
- The finance core.
Required Texts & Learning Materials There is no textbook required for this course. The lecture notes and the references to articles in the notes should suffice for the class.
Recommended Text(s)
- An old reference is John Y. Campbell, Andrew W. Lo, and A. Craig MacKinlay, 1996, Econometrics of Financial Markets, Princeton University Press. ISBN 9780691043012;
- A classic on asset pricing is by John Y. Campbell, 2017, Financial Decisions and Markets: A Course in Asset Pricing, Princeton University Press. ISBN 9780691160801;
- An older book on asset pricing is by John Cochrane, 2005, Asset Pricing, Princeton University Press. ISBN 9780691121376;
- A recent article by John Y. Campbell, 2014, Empirical Asset Pricing: Eugene Fama, Lars Peter Hansen, and Robert Shiller;
- Corporate finance applications are surveyed reasonably nicely in B. Espen Eckbo, Ed. 2009. Handbook of Empirical Corporate Finance Volumes 1 and 2. Elsevier. ISBN 9780444532657;
- Textual analysis is a new topic. For it, there is no standard text but the references we provide should be easy to understand.
To access the syllabus and the course material (e.g., lecture notes), please email me at andrea.passalacqua@jhu.edu.