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Financial  Econometrics

Objectives

This course introduces some key topics in financial econometrics. It is designed to help students understand and apply several important contributions in Empirical Finance as well as 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.

This high-paced course will discuss some of the quantitative techniques nowadays considered as state of the art by practitioners of financial markets, such as volatility modeling and forecasting; and in corporate finance. Students will be required to use real data in exercises and to discuss and analyze the results in the classroom.

General characterization

Code

2272

Credits

3.5

Responsible teacher

Paulo M. M. Rodrigues

Hours

Weekly - Available soon

Total - Available soon

Teaching language

English

Prerequisites

Available soon

Bibliography

1. Brooks, C. (2014) Introductory Econometrics for Finance, 3rd/e. 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. Hamilton, James (1994), Time Series Analysis, Princeton University Press;

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

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

7. Wilmott, Paul (2007) Paul Wilmott introduces quantitative finance, 2/e., John Wiley & Sons Ltd.

Resources

Lecture presentation slides will be made available as well as several research articles.

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 three assignments (10%, 10%, 15%) and a final exam (65% - minimum grade requirement 7).

Subject matter

1.    The Characteristics of Financial Data
2.    Time Series Analysis and Forecasting
3.    Modelling and Forecasting Volatility
4.    VaR and Expected Shortfall