- Docente: Luca De Angelis
- Credits: 6
- SSD: SECS-P/05
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Quantitative Finance (cod. 8854)
Learning outcomes
At the end of the course the student is introduced to the basic concepts of econometrics, with particular focus on time series analysis. The student masters the basic least squares and maximum likelihood techniques. As for time series analysis, the student is able to apply standard ARIMA methods, with introduction to fractional integration. The student learns to apply these models using Mathlab.
Course contents
1. Moment-conditions based estimation. Least squares and quasi maximum likelihood
2. Large-sample OLS-based inference in linear models with stochastic regressors
3. Large-sample quasi maximum likelihood inference
4. Univariate time series models for conditional means and conditional variances. Estimation and inference
Important remark. For the successful completion of the course, students are highly recommended to have followed an elementary introduction to econometrics, at the level of Chapters 4-7 of Stock and Watson's Introduction to Econometrics (3d edition). These chapters are suitable for self study by students with no preliminary exposure to econometrics. Students are also expected to be familiar with matrix algebra.
Readings/Bibliography
Hansen B. (2020). Econometrics (download here)
Tsay R. (2002). Analysis of Financial Time Series. Wiley
Teaching methods
Traditional lectures, empirical examples and analyses in a computer lab
Assessment methods
Written exam consisting of five questions regarding two parts: theoretical exercises and questions based on estimation output.
Teaching tools
Econometric software: Gretl
Office hours
See the website of Luca De Angelis