- Docente: Luca De Angelis
- Credits: 5
- SSD: SECS-P/05
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: First cycle degree programme (L) in STATISTICAL SCIENCES (cod. 8054)
Learning outcomes
The aim of the course is to provide basic techniques for constructing econometric models, with applications to finance and economic forecasting.
Course contents
Part 1: forecasting techniques
General concepts. Statistical and theoretical information. Quantitative and qualitative methods. Forecast horizon, loss function, information set and predictability. Exogeneity.
Econometric models for short-term forecast. Dynamic models: estimation, testing, specification analysis and forecasting. Multivariate models: vector autoregressive models (VAR), impulse-response functions, variance decomposition.
Part 2: Financial Markets
Econometric models for prices and returns. Modeling conditional heteroskedasticity: ARCH models. Extensions: GARCH, exponential GARCH, asymmetric GARCH and GARCH “in mean”. Estimation, testing and specification analysis. News impact curve. forecasting volatility.
Econometric models for measuring risk. the Value-at-Risk (VaR). Estimating the VaR: J.P. Morgan's “Risk metrics”. Econometric methods for VaR estimation: GARCH models. Monte Carlo methods and historical simulation.
Readings/Bibliography
Diebold, F.X. (2001), Elements of forecasting, South Western/Thomson Learning.
Campbell, J.Y., Lo, A. and A.C. MacKinley (1997), The Econometrics of Financial Markets, Princeton University Press.Teaching methods
All topics are illustrated with economic data using some econometric packages.
Assessment methods
Written and oral exam.
Teaching tools
Computer lab.
Links to further information
http://www2.stat.unibo.it/deangelis/didattica.htm
Office hours
See the website of Luca De Angelis