75367 - Econometrics

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

The course aims to provide foundational concepts in econometric methodology and analysis, which form the essential framework for the empirical analysis of financial markets and their stylized facts. The content is structured as follows:

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

5. Empirical applications: case studies and applications to financial markets; construction of conditional Value-at-Risk 

The discussion of all theoretical results will be supported by a series of practical exercises designed to aid in the application of different theoretical aspects to real-world empirical issues.

 

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

Lecture notes will be made available throughout the course, accompanied by additional materials, data sets, and a list of exercises. These resources will be posted on Virtuale and will support the understanding of course content and provide practical opportunities for applying the concepts covered during the lectures.

Suggested readings:

Sheppard K. (2021). Financial Econometrics Notes.

Tsay R. (2002). Analysis of Financial Time Series. Wiley

Teaching methods

Traditional lectures, empirical examples and analyses in a computer lab

Assessment methods

This course is part of the Integrated Course "Stochastic Processes and Econometrics". 

The assessment for the Econometrics' part consists in a written exam of three questions divided into two sections: theoretical exercises and questions based on estimation output. Each question is drawn from the topics covered in course lectures and labs. Two questions are worth a maximum of 12 points each, while the third is worth 8 points, totaling 32 points. The duration of the exam is approximately 1 hour. 

To pass the exam a minimum grade of 15/30 is required. The final grade for the course "Stochastic Processes and Econometrics" is obtained by taking the arithmetic mean of the grades achieved in the two different parts of the course. This arithmetic mean must be at least 18/30.

Teaching tools

Notes on digital whiteboard and slides

Econometric software: Gretl

Office hours

See the website of Luca De Angelis