This 10 credit module aims to provide students with an understanding and appreciation of recent developments in empirical finance. The module focuses on empirical modelling techniques and the interpretation of empirical results. It will cover volatility modelling with GARCH and its extensions; asset pricing and factor models; empirical analysis of risk; Logit and Probit analysis for corporate financeequity dynamics and returns; empirical analysis of finance-macroeconomics nexus (interest rate, inflation, the housing market etc.).

• Establish fundamental concepts in econometrics for financial mathematics;

• Command of econometric modelling techniques

• Set out hypothesis tests

• Utilize estimation techniques and conduct robustness checks

Modules will be delivered through blended learning. You will be guided through learning activities appropriate to your module, which may include:

• Weekly face to face classes (e.g. labs, lectures, exercise classes)
• Electronic resources that you work through at your own pace (e.g. videos, exercise sheets, lecture notes, e-books, quizzes)

Students are also expected to undertake self-guided study throughout the duration of the module.

Skills:
Form the knowledge of the Markovian process and other point process and ability to explain the features and classic examples of these processes; skills to apply econometric modelling techniques to evaluate and interpret financial time series behaviour.

Transferable Skills:
Quantitative skills
Analytic skills
Modelling skills
Oral/discussion skills
Development of independence and autonomy
Questioning skills
Learning skills
Problem solving skills

1. Basic linear regression theory.

2. Asset pricing models and simple forecasting modelling.

3. Logit/Probit models & marginal effects.

4. Stationarity/non-stationarity, integration

5. Elementary non-linear modelling

6. Introduction to cross-section models.