Module Lead: Nicholas Horsewood
Credits: 20
Introduction and module objectives
This module will provide students with an understanding of modern advanced econometric procedures, with emphasis placed on interpreting econometric results and critically evaluating the techniques employed. In the first semester there will be a technical review of the classical linear model, examining the implications when the key assumptions are violated. This will be followed by a general survey of the main techniques in the applied literature. Both computer and econometric classes will be support the lectures, providing utilise these for specific practical problems.
The second half of the module will focus on application of econometric techniques in finance. It will look at stationary time series processes, difference stationary processes, the analysis of Vector Autoregressions (VAR), Cointegration, Generalised Autoregressive Conditionally Heteroskedastic (GARCH) models.
Learning outcomes:
By the end of the module the student should be able to:
- demonstrate a comprehensive knowledge and understanding of traditional econometrics;
- identify and critically appraise recent developments in advanced econometrics techniques and their application;
- synthesise econometric studies in the empirical literature and critically analyse the results and the approaches adopted;
- develop and analyse models for stationary and non-stationary time series;
- critically evaluate the techniques employed in finance journals.
Assessment:
- Two 1 hour multiple choice tests (40%)
- Three hour written examination (60%)