MSc Quantitative Finance
Year of entry: 2023
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Course unit details:
Time Series Econometrics
|Unit level||FHEQ level 7 – master's degree or fourth year of an integrated master's degree|
|Teaching period(s)||Semester 2|
|Offered by||Alliance Manchester Business School|
|Available as a free choice unit?||No|
Time series data is heavily exploited in empirical and quantitative finance as historical information contained in past data can be useful in predicting future behaviour of financial markets. This leads to the development of time series econometrics, a subject dedicated to modelling, analysing and forecasting time series data. In modern financial markets, time series methods play a central role in technical analysis of asset pricing, risk management and portfolio management.
This course begins with an overview of some stylized facts of financial time series data, followed by a rigorous and comprehensive treatment on the theory of time series. The course continues with a series of lectures covering classical univariate and multivariate time series models such as ARIMA, VAR and GARCH, and extending to advanced topics such as high-frequency financial econometrics and regime-switching models. Each lecture is accompanied with a MATLAB session to demonstrate real data application of the covered models.
The aims of this course are to introduce students to important econometric techniques that are used in time series analysis and to facilitate awareness in students of how these techniques can be used and applied in empirical finance.
On completion of this unit successful students will have achieved the following learning outcomes:
- A detailed knowledge and understanding of advanced techniques and skills in time series Econometrics
- A systematic knowledge and understanding of issues at the forefront of research a practice in finance
- A knowledge and understanding of basic research skills and empirical methods in finance
- The working knowledge of MATLAB programming and implementation of time series methods
|Written assignment (inc essay)||80%|
Examination - 80%
Group Coursework - 20%
Informal advice and discussion during a lecture, seminar, workshop or lab.
Online exercises and quizzes delivered through the Blackboard course space.
Responses to student emails and questions from a member of staff including feedback provided to a group via an online discussion forum.
Written and/or verbal comments on assessed or non-assessed coursework.
Generic feedback posted on Blackboard regarding overall examination performance.
Peter J. Brockwell & Richard A. Davis (2016), Introduction to Time Series and Forecasting, 3rd edition, Springer
Taylor, S. J. (2009) Asset Price Dynamics, Volatility, and Prediction. Princeton University Press. Princeton.
These texts cover the majority of the material delivered in this course unit. It is strongly advised that you purchase these texts. Older versions of the texts also cover the most of the material.
In addition to these recommended texts you should undertake supplementary reading of appropriate econometric texts where necessary to support your learning. In particular, you may find the following texts useful:
Ruey S. Tsay (2010) 3rd ed., Analysis of Financial Time Series, Wiley.
Mikosch, T., Kreiß, J. P., Davis, R. A., and Andersen, T. G. (2009) Handbook of financial time series. Berlin: Springer.
Brockwell, Peter J. & Davis, Richard A. (1991) Time series: theory and methods.
2nd ed. New York, Springer.
|Scheduled activity hours|
|Assessment written exam||3|
|Independent study hours|
|Aleksey Kolokolov||Unit coordinator|
|Sungjun Cho||Unit coordinator|
|Yifan Li||Unit coordinator|
Informal Contact Methods
Online Learning Activities (Blogs, discussions, self-assessment questions)
Drop in Surgeries (extra help sessions for students on material they may be struggling with)