Module and Programme Catalogue

Search site

Find information on

2018/19 Taught Postgraduate Module Catalogue

MATH5350M Computations in Finance

15 creditsClass Size: 70

Module manager: Dr Jitse Niesen
Email: J.Niesen@leeds.ac.uk

Taught: Semester 2 View Timetable

Year running 2018/19

Pre-requisite qualifications

Intermediate knowledge of programming in C or C++ or other appropriate language. C/C++ implementations of numerical algorithms will be required in assessed courseworks. No training in programming will be provided.

Co-requisites

MATH5330MContinuous Time Finance

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;
- explain techniques for improving simulation accuracy and efficiency;
- demonstrate an understanding of numerical methods for PDEs;
- use finite difference methods to price European and American options;
- estimate price sensitivities (the Greeks).

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 typeNumberLength hoursStudent hours
Lecture112.0022.00
Practical31.003.00
Seminar111.0011.00
Private study hours114.00
Total Contact hours36.00
Total hours (100hr per 10 credits)150.00

Private study

- 5 hours per lecture: 55 hours
- 5 hours per class: 55 hours
- Preparation 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 typeNotes% of formal assessment
In-course Assessment.40.00
Total percentage (Assessment Coursework)40.00

The resit for this module will be 100% by examination


Exams
Exam typeExam duration% of formal assessment
Standard exam (closed essays, MCQs etc)2 hr 00 mins60.00
Total percentage (Assessment Exams)60.00

The resit for this module will be 100% by 2 hours examination

Reading list

The reading list is available from the Library website

Last updated: 12/12/2018 10:48:54

Disclaimer

Browse Other Catalogues

Errors, omissions, failed links etc should be notified to the Catalogue Team.PROD

© Copyright Leeds 2019