- Docente: Emanuele Bacchiocchi
- Credits: 6
- SSD: SECS-P/05
- Language: English
- Teaching Mode: Traditional lectures
- Campus: Bologna
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Corso:
Second cycle degree programme (LM) in
Greening Energy Market and Finance (cod. 5885)
Also valid for Second cycle degree programme (LM) in Applied Economics and Markets (cod. 5969)
Second cycle degree programme (LM) in Quantitative Finance (cod. 8854)
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from Sep 18, 2025 to Oct 17, 2025
Learning outcomes
At the end of the course the student is able to develop the econometric analysis of the class of present value models used in financial econometrics, using stationary and/or non-stationary Vector Autoregressive systems as statistical platforms upon which all theoretical restrictions are nested and tested.
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 failed18-23 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