Aims and Fit of Module

The aim of this module is to introduce state of the art models and computational techniques widely used in quantitative finance and financial engineering with extensive programming.

Learning outcomes

A. Understand, analyze and implement (with coding in MATLAB/Excel VBA/C++) Monte Carlo (MC/QMC/RQMC) simulation, generation of random variables, simulation of stochastic processes, discretization schemes, variance reduction techniques.
B. Understand, analyze, and implement numerical techniques (with coding in MATLAB/Excel VBA/C++) and models in pricing options, interest rate, and credit products.
C. Understand, analyze and implement (with coding in MATLAB/Excel VBA/C++) fundamental numerical techniques in portfolio optimization and risk quantification applications.
D. Understand, explain, and implement results from selected literature on computational finance.

Method of teaching and learning

Lectures and computer labs using the software MATLAB/Excel VBA/C++, Article Readings (max of 5) related to lecture materials