Module code: MTH7026P
Credits: 15.0
Semester: SEM1
Contact: Mr Christopher Sutton
This module introduces necessary analytical tools for risk management. After an introduction on basic statistics and probability used in physical and life sciences and economics, we give an overview of various loss distribution models, which are applied to liability valuations. We then discuss compound distributions and their applications in risk modelling. To manage dependent and extreme risks, we discuss copulas and extreme value theory. We also discuss stochastic modelling and stochastic processes. It covers discrete time processes including Markov chains and random walks, and continuous time processes such as Poisson processes. This module includes real-world data application using R.
This module lays the mathematical foundation for risk management, and prepares you to be professional risk managers and actuaries in global business environments.
Connected course(s): UDF DATA
Assessment: 80.0% Examination, 20.0% Coursework
Level: 7
