Unit name | Financial Time Series |
---|---|
Unit code | MATHM0025 |
Credit points | 10 |
Level of study | M/7 |
Teaching block(s) |
Teaching Block 2D (weeks 19 - 24) |
Unit director | Dr. Yu |
Open unit status | Not open |
Pre-requisites | |
Co-requisites |
None |
School/department | School of Mathematics |
Faculty | Faculty of Science |
Unit aims
This course aims to cover
General Description of the Unit
This course builds on the Level 6 MATH33800 Time Series Analysis course which describes classical stationary linear time series analysis, moves onto non-linear and non-stationary time series with an emphasis in modelling financial time series, and is concluded with a brief introduction on statistical methods used in high-frequency trading. This course aims to provide both rigorous theoretical justifications of GARCH models and error correction models, and also systematic data analysis tools from data visualisation to model evaluation, when GARCH effects or co-integration phenomenon is presented. This course will conclude with a brief introduction of statistical methods used in high-frequency financial time series, but will not cover detailed theory proofs.
Relation to Other Units
This course builds on MATH33800, Time Series Analysis.
Additional unit information can be found at http://www.maths.bristol.ac.uk/study/undergrad/current_units/index.html
Learning Objectives
At the end of the unit the student should be able to
Transferable Skills
The ability to know when different time series models work and fit suitable models are highly valued in many areas, especially in finance.
Lectures (with encouraged audience participation) plus regular formative problem and solution sheets. Some of the questions on the problem sheets will be to do with practical data analysis.
100% Examination.
1.5 hours
Raw scores on the examinations will be determined according to the marking scheme written on the examination paper. The marking scheme, indicating the maximum score per question, is a guide to the relative weighting of the questions. Raw scores are moderated as described in the Undergraduate Handbook.
Recommended reading:
Brockwell, P.J. and Davis, R.A., Time Series: Theory and Methods. Springer, (2009)
Andersen, T.G. and Davis, R.A., Handbook of Financial Time Series, Springer, (2009)
Leung Lai, T. and Xing, H., Statistical Models and Methods for Financial Markets, Springer, (2008)