2007/08 Taught Postgraduate Module Catalogue
MATH5350M Computations in Finance
15 creditsClass Size: 100
Module manager: Klaus Reiner Schenk-Hoppé
Email: K.R.Schenk-Hoppe@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2007/08
This module is not approved as an Elective
Objectives
The aim of this module is to introduce the standard computational methods in financial mathematics and their application to securities pricing. There is a strong emphasis on practical implementation and numerical simulation. On completion of this module, students will be able to:- explain the basic modelling tools for financial options;
- generate random numbers with specified distributions;
- numerically solve stochastic differential equations;
- carry out Monte Carlo simulations to price financial derivatives;
- demonstrate an understanding of numerical methods for PDEs;
- use finite difference methods to price American and exotic options;
- explain techniques for improving simulation accuracy and efficiency;
- estimate price sensitivities (the Greeks) and market risk.
Syllabus
Pricing financial instruments and valuing new securities requires advanced numerical methods. Financial analysts routinely apply computational techniques to assess risk, price exotic options or value interest rate derivatives. A good command of the essential computational tools used in the financial service industry is expected from quantitative analysts.
This module covers Monte Carlo simulations and finite difference methods for financial derivative pricing. These two methods (both are standard workhorses) are essential in analysing securities that are modelled by stochastic or partial differential equations. Practical skills are emphasised and students will learn how to implement (and improve accuracy and efficiency of) numerical methods for financial valuation.
On completion of this module the student will be familiar with numerical methods in financial mathematics and will be able to apply and implement these methods to price financial derivatives.
Teaching methods
Delivery type | Number | Length hours | Student hours |
Lecture | 10 | 2.00 | 20.00 |
Practical | 10 | 1.00 | 10.00 |
Private study hours | 120.00 | ||
Total Contact hours | 30.00 | ||
Total hours (100hr per 10 credits) | 150.00 |
Private study
5 hours per lecture: 50 hours;5 hours per class: 50 hours;
Prepararion for assessment: 20 hours.
Opportunities for Formative Feedback
Exercises will be handed in for assessment on a bi-weekly basis.Methods of assessment
Coursework
Assessment type | Notes | % of formal assessment |
In-course Assessment | Assessed exercises | 30.00 |
Total percentage (Assessment Coursework) | 30.00 |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Exams
Exam type | Exam duration | % of formal assessment |
Standard exam (closed essays, MCQs etc) | 2 hr | 70.00 |
Total percentage (Assessment Exams) | 70.00 |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Reading list
The reading list is available from the Library websiteLast updated: 24/06/2009
Browse Other Catalogues
- Undergraduate module catalogue
- Taught Postgraduate module catalogue
- Undergraduate programme catalogue
- Taught Postgraduate programme catalogue
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