UnitLevel 5Postgraduate

MTH5530 Computational methods in finance

Faculty of Science

MTH5530 Computational methods in finance is a level 5, 6-credit-point, postgraduate unit from the Faculty of Science, offered in 2022 in Semester 1 at Clayton. It has no prerequisites.

Credit points
6
Offered in 2022
Semester 1
Clayton
Assessment
Exam 60%
and 1 other task

This is the 2022 handbook entry. See the 2027 entry.

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Requisites

Before MTH5530

No prerequisites or corequisites besides the enrolment rules below.

After MTH5530

No unit lists MTH5530 as a prerequisite in the 2022 handbook.

Enrolment rules

COREQUISITE: Only students enrolled in the Master of Financial Mathematics and the Master of Mathematics can enrol in this unit. Exceptions can be made with permission from the unit coordinator.

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 in 2022

Teaching periodCampusMode
First semesterClaytonOn campus

Assessment

  • Assignments and homeworkAssignment
    40%
  • Examination (3 hours and 10 minutes)ExamThreshold hurdle
    60%

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    Develop specialised mathematical knowledge and computational skills within the fields of partial differential equations and probability theory.

  2. 2

    Understand the complex connections between specialised financial and mathematical concepts.

  3. 3

    Apply critical thinking to problems in partial differential equations that relate to financial derivatives.

  4. 4

    Apply computational problem solving skills within the finance context.

  5. 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. 6

    Communicate complex information in an accessible format to a non-mathematical audience.

Workload and teaching

  • Lectures36 hours
  • Applied sessions11 hours
  • Teaching approachActive learning
  • Two 1.5 -hour lectures;
  • One 1-hour applied class (in weeks 2-12) and
  • Eight hours of independent study per week.

This is an established way to teach high-level abstract mathematics effectively. In this model, you are expected to revise the theory explained in the lectures at home. This active learning process will assist students in fully understanding the new concepts.

Learning resources

Required resources

Part 2 (Numerical linear algebra): Briggs, William L., and Steve F. McCormick. A multigrid tutorial . Vol. 72. SIAM, 2000.

Contacts

Chief Examiners
Dr Tiangang Cui
Unit Coordinators
Dr Tiangang Cui

Common questions

What are the prerequisites for MTH5530?

MTH5530 has no prerequisites, but enrolment rules apply.

When is MTH5530 offered?

In 2022, MTH5530 runs in Semester 1 at Clayton.

Does MTH5530 have an exam?

Yes. The exam is worth 60% of the final mark, alongside 1 other task.

More details

Credit points
6
Level
5
Study level
Postgraduate
Faculty
Faculty of Science
Organisational unit
School of Mathematics
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 1
Study abroad
Available