Course unit details:
Financial Econometrics
Unit code | ECON60332 |
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Credit rating | 15 |
Unit level | FHEQ level 7 – master's degree or fourth year of an integrated master's degree |
Teaching period(s) | Semester 2 |
Available as a free choice unit? | No |
Overview
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.
Aims
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.
Learning outcomes
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
Syllabus
Provisional
- Linear Models (OLS, MLE), Overview of Statistics
- Univariate/Multivariate Linear Time Series Analysis
- Properties of Financial Data
- Volatility Modelling
- Value-at-Risk and Forecasting
- High-Frequency Data and Market Microstructure
- Realized Variance
- Portfolio allocation and multivariate risk modelling
Teaching and learning methods
Lectures and tutorials
Knowledge and understanding
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
Assessment methods
Method | Weight |
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Written exam | 80% |
Written assignment (inc essay) | 20% |
Recommended reading
Main textbooks:
Tsay Ruey S. (2010): Analysis of Financial Time Series, 3rd 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
Study hours
Scheduled activity hours | |
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Lectures | 20 |
Tutorials | 10 |
Independent study hours | |
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Independent study | 120 |
Teaching staff
Staff member | Role |
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Arthur Sinko | Unit coordinator |
Additional notes