The M.Com Financial Economics Bridging Courses can be found here.

**Course Outline:**

The main purpose of this page is to provide master’s students in financial economics with knowledge they will need to conduct cutting edge research in the broad areas of financial economics namely financial econometrics, risk management, asset allocations and portfolio optimization. It is assumed that students studying toward a master's degree in financial economics have a good background in mathematical statistics, financial econometrics and probability theory. The modules I teach cover the following topics:

- Non-parametric econometrics: univariate and multivariate kernel regression;
- Risk management: value at risk estimation, extreme value distributions, copulas, market, operational and credit risk modeling;
- Portfolio selection: modern portfolio theory i.e. the mean-variance portfolio model and its alternatives;
- Bayesian methods in Finance: Bayesian CAPM, Bayesian GARCH models, Bayesian portfolio selection, The Black Litterman model, and the Bayesian risk management.
- Advances in behavioural finance: probability weighting, loss aversion, behavioural asset pricing and behavioural portfolio theory.

The following software will be used:

- Matlab software with statistics and optimization toolboxes fully installed,
- R software with all default packages duly installed
- WinBUGS

Although I will help you with some Matlab and R programming, I expect you to write your own Matlab/R programs in order to develop your own models.

**Informative Lessons**

You are also adviced to watch these financial videos in order to familiarise yourself with the topics that will be discussed in this course.

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__Links to Some Useful eBooks in html Version__:

Applied Quantitative Finance

Statistical Tools for Finance and Insurance

Statistics of Financial Markets

Applied Multivariate Statistical Analysis

Nonparametric and Semiparametric Models

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