MTH5530 · Computational methods in finance

Overview

The overall aim of this unit is to study the fundamental computational methods for solving problems in financial mathematics. This includes a full overview of finite-difference methods for obtaining numerical solutions of partial differential equations, convergence and stability analysis of finite-difference methods, iterative techniques for solving large-scale linear systems arising from numerical solutions of PDEs, the Black-Scholes equation and stochastic volatility models, option pricing, Monte Carlo computation, and selected topics in mathematical finance.

Offerings

Assessment

The Handbook lists an examination for this unit.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. Develop specialised mathematical knowledge and computational skills within the fields of partial differential equations and probability theory;
2. Develop and understand the complex connections between specialised financial and mathematical concepts;
3. Apply critical thinking to problems in partial differential equations that relate to financial derivatives;
4. Apply computational problem solving skills within the finance context;
5. Formulate expert solutions to practical financial problems using specialised cognitive and technical skills within the fields of partial differential equations and probability theory;
6. Communicate complex information in an accessible format to a non-mathematical audience.

Workload

• Two 1.5 -hour seminars; • One 1-hour applied class (in weeks 2-12) and • Eight hours of independent study per week.

Student experience, not official rules. Nothing here changes what the Handbook says.