37270 - ECONOMETRICS OF FINANCIAL MARKETS

Learning outcomes

This course aims to provide students with a comprehensive understanding of the econometric techniques used in financial economics. It explains the nature of time series econometrics and demonstrates applications in business, economics and finance. Specifically, the course focuses on issues such as: stationarity, cointegration and error correction models, time varying volatility models, structural VAR models. Strong emphasis will be placed on the practical application of such models to real financial and economic data. Some computer software packages will be used to estimate models and perform diagnostic tests. At the end of the course the student is expected to develop the skills to read and understand empirical research, and to conduct econometric analysis and empirical research.

Course contents

Financial Time Series and Their Characteristics

Asset Returns

Distributional Properties of Returns

Distributions of Returns

Multivariate Returns

Likelihood Function of Returns

Empirical Properties of Returns

Conditional Heteroscedastic Models

Characteristics of Volatility

Testing for ARCH Effect

The ARCH Model

The GARCH Model

Further developments of GARCH models

The Stochastic Volatility Model

Nonlinear Models and Their Applications

Threshold Autoregressive (TAR) Model

Smooth Transition AR (STAR) Model

Markov Switching Model

Neural Networks

Nonlinearity Tests

Quantile Estimation and Value at Risk

Value at Risk

An Econometric Approach to VaR Calculation

Quantile Estimation

Quantile and Order Statistics

Quantile Regression

Principal Component Analysis and Factor Models

A Factor Model

Macroeconometric Factor Models

Principal Component Analysis

Structural Autoregressive (SVAR) models

Review of stationary and cointegrated VAR models

Econometric models: reduced form and structural form

SVAR models and the identification issue

Equality restrictions and sign restrictions

Global, local and set identification in SVAR models

Impulse response functions and Forecast Error Variance Decomposition

Readings/Bibliography

Suggested literature

Books:

- Analysis of Financial Time Series – Ruey S. Tsay

- Applied Economic Forecasting using Time Series Methods – E. Ghysels and M. Marcellino

- Introductory Econometrics for Finance - Chris Brooks

- A Guide to Modern Econometrics - Marno Verbeek

Notes:

- Time Series for Macroeconomics and Finance - John Cochrane

- Econometrics - Bruce Hansen

Papers:

- The Use of ARCH/GARCH Models in Applied Econometrics – Robert Engle

- Structural Vector Autoregressions - Lutz Kilian

Teaching methods

Teaching lessons and empirical exercises using the econometric software Gretl.

Assessment methods

The final exam aims at evaluating the achievement of the following educational targets:

- knowledge of the econometric techniques shown during the frontal lectures

- ability to employ these techniques to analyse and interpret economic and financial phenomena

The exam consists of a written test.

In case online exams will be envisaged by the University of Bologna, the structure of the written exam is the same. The exam will be run through Zoom and Exams Online (EOL). Detailed instructions on how to manage and hand in the online exam are available on the course page on the VIRTUALE platform.

The maximum possible score is 30 cum laude, in case all answers are correct, complete and formally rigorous.

The grade is graduated as follows:

<18 failed
18-23 sufficient
24-27 good
28-30 very good
30 e lode excellent

Teaching tools

Empirical exercises using the econometric software Gretl. All the material (codes and data) used during the empirical exercises will be available from the Virtuale platform dedicated to the course.

Office hours

See the website of Emanuele Bacchiocchi