| Unit name | Advanced Time Series |
|---|---|
| Unit code | MATHM6003 |
| Credit points | 10 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Professor. Nason |
| Open unit status | Not open |
| Pre-requisites |
None |
| Co-requisites |
None |
| School/department | School of Mathematics |
| Faculty | Faculty of Science |
Time series are measurements on variables collected over time. The focus of this course will be on the analysis and forecasting of financial time series, by which we mean, for example, stock indices, share prices or currency exchange rates, amongst others. Of great interest to market practitioners and theoretical statisticians alike is the ability to understand the structure and forecast time series of this type. To do this, usually a probabilistic model is required. This course will introduce two families of models designed to handle financial time series: stationary nonlinear models, and locally stationary linear models.
