Introductory description

In this module, students will learn the main econometric techniques for performing cross-sectional, time series, and panel data analyses.Students will be trained to use software to practically implement estimation and testing in the context of the econometrics of financial markets.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Indicative syllabus:
Introduction to probability and statistical inference;
Classical linear regression models;
Introduction to maximum likelihood estimation;
Discrete choice models;
Models for panel data;
Introduction to time-series analysis.

Learning outcomes

By the end of the module, students should be able to:

• Demonstrate complete understanding of the principles behind econometric/ statistical tools
• Demonstrate understanding of which quantitative methods and statistical techniques to apply in most situations when analysing financial data.
• Critically evaluate and replicate empirical studies published in both academic and practitioners journals.

Indicative reading list

Jeffrey M. Wooldridge,Introductory Econometrics A Modern Approach, 7th edition, South Western College, 2019.

Subject specific skills

Select the most appropriate modelling specification and econometric setup for any given research question.
Handle various econometric techniques at an intermediate level.
Carry out robust empirical studies and analysis for cross-sectional, time-series and panel data.

Transferable skills

Written communication
Numeracy