Econometrics for Financial Markets 2021/2022

Academic Year 2021/2022

Learning outcomes

At the end of this course, the student will know the key elements behind the quantitative analysis of financial markets. The student will be able to specify, estimate and interpret econometric models intended to explain the dynamics of prices, returns and volatility of financial assets. The student will also be able to carry out empirical analyses with econometric packages.

Course contents

1) Introduction:

- Statistical analysis of economic relationships.

- How to build an econometric model.

2) Linear regression model:

- OLS

- Estimation issues: classic and generalized model.

- Diagnostic analysis.

- Heteroskedasticity and autocorrelation.

3) Maximum likelihood estimator.

4) ARMA models.

5) Models for conditional volatility.

6) Endogeneity and instrumental variables.

Readings/Bibliography

Teachers will also provide their own teaching materials made available on IOL.

Reference books:

Marno Verbek, A Guide to Modern Econometrics

Ruey S Tsay, Analysis of Financial Time Series (only for point 5 of the program: Models for conditional volatility).

Teaching methods

Classes and labs using Matlab

Assessment methods

The exam aims to verify thjat the student has achieved the following basic targets:

• knowledge of basic econometrics, in particular, the special features which characterize financial markets;

• the ability to apply the main theoretical concepts to modeling asset returns and their volatility.

The exam is written and a grade of the form xx/30 is given.

Students are supposed to do theoretical exercises but also discuss practical cases based on estimation outputs which refer to real markets.

Teaching tools

Econometric software: Matlab

Links to further information

https://sites.google.com/view/giovanni-angelini/home

Office hours

See the website of Giovanni Angelini

13178 - Econometrics for Financial Markets

Course Unit Page

SDGs