Introductory description

The module aims to provide students with an in-depth understanding of and key skills in basic probability and distribution theory; basic statistical estimation and inference; and econometric models with applications to finance

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:

• Be aware of quantitative methods and statistical techniques to apply in most situations when analysing financial data.
• Understand the basic principles behind the econometric/statistical tools introduced in the course.
• Select the most appropriate modelling specification and econometric setup for any given research question.
• Successfully perform empirical analysis in finance at an intermediate level.

Indicative reading list

Jeffrey M. Wooldridge,Introductory Econometrics A Modern Approach, 4th edition, South Western College, 2008.

Subject specific skills

Handle various econometric techniques at an intermediate level.
Carry out robust empirical studies for cross-sectional, time-series and panel data.
Understand, critically evaluate and replicate empirical studies published in both academic and practitioners journals.

Transferable skills

Design empirical projects and evaluate different econometric techniques critically.