2018/19 Taught Postgraduate Module Catalogue
MATH5360M Optimisation Methods for Finance
15 creditsClass Size: 70
Module manager: Dr Graham Murphy; Dr James Fung
Email: G.J.Murphy@leeds.ac.uk; J.C.L.Fung@leeds.ac.uk
Taught: Semester 1 View Timetable
Year running 2018/19
Pre-requisite qualificationsThe qualifications to gain entrance to the MSc in Financial Mathematics are sufficient.
This module is not approved as an Elective
ObjectivesTo provide students with the analytical and numerical skills required to solve optimisation and derivative pricing problems in finance.
On completion of this module, students will be able to:
- write algorithms for solution of mathematical and finance related tasks;
- write simple programmes for solution of mathematical and finance-related tasks;
- explain in detail convex sets and functions, constrained and unconstrained maximisation problems, global and local extrema;
- describe linear programming problems;
- demonstrate an understanding of Lagrange multipliers;
- solve linear programming problems numerically;
- describe quadratic programming problems;
- demonstrate an understanding of numerical algorithms forsolving quadratic programming problems;
- solve mean-variance optimisation problems;
- demonstrate an understanding of simple stochastic programming problems;
- solve simple asset-liability management problems;
- apply optimisation methods in risk management.
Computer programming, algorithms, numerics, optimisation techniques, applications in portfolio and risk management
Portfolio choice, risk management and pricing of financial derivatives require solving optimisation problems. The module will develop the relevant mathematical tools, numerical methods and programming skills for analysing and solving optimisation problems in finance.
The module covers linear, quadratic and stochastic programming. Practical applications include arbitrage-free pricing of options, optimisation of risk measures, calculation of optimal portfolios, applications to asset-liability management and risk management. The module provides an introduction to a programming language.
|Delivery type||Number||Length hours||Student hours|
|Private study hours||110.00|
|Total Contact hours||40.00|
|Total hours (100hr per 10 credits)||150.00|
Private study4 hours per lecture
2 hours per tutorial
1 hours per practical
40 hours Preparation for assessment
Opportunities for Formative FeedbackProgress will be monitored by contributions made to tutorials and during practicals; performance in ACWs.
Methods of assessment
|Assessment type||Notes||% of formal assessment|
|Total percentage (Assessment Coursework)||40.00|
The resit for this module will be 100% by 2 hours examination
|Exam type||Exam duration||% of formal assessment|
|Standard exam (closed essays, MCQs etc)||2 hr||60.00|
|Total percentage (Assessment Exams)||60.00|
The resit for this module will be 100% by 2 hours examination.
Reading listThe reading list is available from the Library website
Last updated: 30/09/2019
Browse Other Catalogues
- Undergraduate module catalogue
- Taught Postgraduate module catalogue
- Undergraduate programme catalogue
- Taught Postgraduate programme catalogue
Errors, omissions, failed links etc should be notified to the Catalogue Team.PROD