Empirical Methods for Finance


This course introduces some key topics in empirical finance. It is designed to help students understand and apply several important contributions as well as introduce the quantitative tools used in the real world by analyst, managers and other professionals in finance. As a consequence of the regulatory changes (e.g., Basel III Accord) there is a growing demand in the financial industry for people with quantitative skills who are able to understand and apply these techniques on financial data, analyze results, and elaborate reports. Furthermore, the ability to synthesize information into a few, easy to interpret statistics is an invaluable analytical tool. This course will emphasize solid foundations and major empirical applications with real data.
Students will be required to use real data in exercises and to discuss and analyze the results in the classroom. Students will also be introduced to programming in STATA.

General characterization





Responsible teacher

Paulo M. M. Rodrigues


Weekly - Available soon

Total - Available soon

Teaching language



Available soon


1.    Brooks, C. (2019) Introductory Econometrics for Finance, 4th edition. Cambridge University Press, New York;

2.    Campbell, Lo and MacKinlay,(1997) The Econometrics of Financial Markets” Princeton University Press;

3.    Gourieroux, C. and J. Jasiak (2001) Financial Econometrics, Princeton University Press;

4.    Tsay, Ruey S. (2002), Analysis of Financial Data, Wiley;

5.    Wang, P. (2009) Financial Econometrics, 2nd Ed. Routledge;

6.    Wilmott, Paul (2007) Paul Wilmott introduces quantitative finance, 2nd edition, John Wiley & Sons Ltd.

7.    Wooldridge, J.M. (2013). Introductory econometrics: A modern approach (5th edition). Mason, OH: South-Western, Cengage Learning.

Teaching method

While lectures cover the core materials, it is important that students supplement classroom time with pre-class preparation, through independent study. Background reading is expected

Evaluation method

Students will be assessed on two assignments (30%) and a final exam (70% - minimum grade requirement 7).

Subject matter

Financial Regression Analysis
I.1    - Simple regression.
I.2    - Multivariate regression.
I.3    - Inference
I.4    - Model specification tests.
I.5    - Instrumental variable regression.