MSc Economics

The aims of this course are to:

(i) enable students to understand recent applied literature in core journals of economics and finance which uses time series methods;

(ii) provide students with the necessary background to conduct applied empirical work using financial data.

The aims of this course are to:

(i) enable students to understand recent applied literature in core journals of economics and finance which uses time series methods;

(ii) provide students with the necessary background to conduct applied empirical work using financial data.

At the end of this course students should be able to:

(i)         identify empirical features and characteristics of various types of financial data

(ii)        utilize various statistical/economic modelling techniques to capture the empirical characteristics of the financial data;

 (iii)       choose and correctly apply proper estimation, testing and forecasting techniques as dictated by the data and selected model;

 (iv)      develop a firm understanding of interrelationships among the data characteristics, modelling techniques and estimation tools;

(v)        extensively use computer software to implement the above methods and apply them to economic data

Provisional

1. Linear Models (OLS, MLE), Overview of Statistics
2. Univariate/Multivariate Linear Time Series Analysis
3. Properties of Financial Data
4. Volatility Modelling
5. Value-at-Risk and Forecasting
6. High-Frequency Data and Market Microstructure
7. Realized Variance
8. Portfolio allocation and multivariate risk modelling

Lectures and tutorials

This is an MSc-level course unit in Financial Econometrics, which therefore assumes that students have previously taken the equivalent of a whole year undergraduate econometrics course, as well as MSc-level econometrics analysis and have a previous knowledge of programming in R

Written exam - 2 hours (70%)

Written assignments x 4 - short coding assignments with analysis of the results (30%)

Written assignments will be 2 x 200 word equivalent (2 x 5%) and 2 x 300 word equivalent (2 x 10%)

Written exam feedback will be provided on the exam script.

Feedback for written assignments will be provided within 2 weeks after submission.

Main textbooks:

Tsay Ruey S. (2010): Analysis of Financial Time Series, 3^rd edition. New York, NY: John Wiley & Sons available online via the Library

Campbell, John Y., Andrew W. Lo, and A. Craig MacKinley (1997). The Econometrics of Financial Markets. Princeton, NJ: Princeton University Press.

Andersen T., Davis R., Kreiß J. and Mikosch T. (2009): Handbook of Financial Time Series, Springer.

Other books on some of the topics covered in the class are

Brooks, C. (2002): Introductory Econometrics for Finance, Cambridge University Press Cambridge

Franses and van Dijk (2000): Nonlinear Time Series Models in Empirical Finance, Cambridge University Press Cambridge.

Gourieroux and Jasiak (2001): Financial Econometrics, Princeton University Press, Princeton.

McNeil, Frey and  Embrechts (2005): Quantitative Risk Management: Concepts, Techniques and Tools, Princeton University Press, Princeton.

As a supplementary reading on time series econometrics, you may find the following texts useful: 

Hamilton, James (1994). Time Series Analysis. Princeton University Press