Dr Xiaolin Zhu

This course is available on the BSc in Actuarial Science, BSc in Data Science and BSc in Mathematics, Statistics and Business. This course is available with permission as an outside option to students on other programmes where regulations permit. This course is not available to General Course students.

Course capped at 60. 

Students must have completed:

EITHER Probability, Distribution Theory and Inference (ST202) OR Probability and Distribution Theory (ST206)

AND Stochastic Processes (ST302).

While the course ST306 is not a formal pre-requisite some examples from this course will be used. Students that have not taken ST306 might have to do a bit of extra reading to familiarise themselves with them.

An introduction to using R for stochastic simulation as well as methods of simulating random variables, complicated quantities involving several random variables and paths of stochastic processes. Applications will focus on examples from insurance and finance.

This course will be delivered through a combination of classes, lectures, help and demonstration sessions totalling a minimum of 30 hours in the  Winter Term. 

Weekly exercises usually involving computing.

• Introducing Monte Carlo methods with R (main reference), by G. Robert and G. Casella.

Useful reading:

• Stochastic Simulation, Algorithms and Analysis by S. Asmussen.
• Monte Carlo Methods in Financial Engineering by P. Glasserman.

Project (40%) in the WT.
Project (60%) in the ST.