Module description
Syllabus
Common families of distributions in financial models, linear regression, time series models, parameter estimation (including least squares and maximum likelihood), simulation.
Prerequisites
Calculus, basic probability theory.
Assessment details
2 hr written examination or alternative assessment
Educational aims & objectives
This module expands the students' toolkit to analyse and model financial risk factors. Statistical models are used in risk management, trading, as well as in contingent claim valuation in incomplete markets, where the focus is on the "real world measure", as opposed to the risk neutral measure. The students will become familiar with some of the many interesting statistical features of financial time series such as non-stationarity, skewness, fat tails, time-varying moments, long-range dependence and stochastic volatility.
Teaching pattern
Two hours of lectures per week
Suggested reading list
Suggested reading/resources (link to My Reading Lists)