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ICM299-Numerical Methods for Financial Engineering
Module Provider: ICMA Centre
Number of credits: 20 [10 ECTS credits]
Level:7
Terms in which taught: Spring term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2022/3
Module Convenor: Dr Peter Sweby
Email: p.k.sweby@reading.ac.uk
Type of module:
Summary module description:
This module is delivered at °ÄÃÅÁùºÏ²Ê¿ª½±¼Ç¼
This module introduces the major numerical methods required for quantitative work in finance, with a particular emphasis on the tools required for the implementation of the major derivative pricing models.
Aims:
This module aims to introduce the major numerical methods required for quantitative work in finance, with a particular emphasis on the tools required for the implementation of the major derivative pricing models, including an introduction to coding in VBA.
Assessable learning outcomes:
By the end of the module, it is expected that students will be able to:
- Understand the basic concepts of numerical approximation
- Solve linear and nonlinear systems of equations
- Implement optimization and calibration methods
- Implement interpolation methods
- Build high standard computer programmes for derivative pricing models using
oÌý Tree-based methods
oÌý Monte C arlo simulation
oÌý Finite Difference methods
Additional outcomes:
Students will learn the fundamental techniques that will enable them to pursue further research in computational finance.
Outline content:
£ Foundations of Numerical Computations
£ Numerical solution of Systems of Linear and Nonlinear Equations
£ Numerical Optimization techniques
£ Calibration methods
£ Interpolation methods
£ Simulation of Stochastic Differential Equations
£ Pricing of financial derivatives Monte Carlo simulations
£ Pricing of financial derivatives with Binomial and Trinomial Trees
£ Pricing of financial derivatives Finite Difference methods
Brief description of teaching and learning methods:
Teaching is via lectures enhanced with practical exercises, with reference to recommended textbooks and journal articles.
Ìý | Autumn | Spring | Summer |
Lectures | 18 | 2 | |
Practicals classes and workshops | 10 | ||
Guided independent study: | Ìý | Ìý | Ìý |
Ìý Ìý Wider reading (independent) | 20 | ||
Ìý Ìý Exam revision/preparation | 20 | 10 | |
Ìý Ìý Advance preparation for classes | 9 | 1 | |
Ìý Ìý Other | 80 | ||
Ìý Ìý Completion of formative assessment tasks | 10 | ||
Ìý Ìý Reflection | 20 | ||
Ìý | Ìý | Ìý | Ìý |
Total hours by term | 0 | 187 | 13 |
Ìý | Ìý | Ìý | Ìý |
Total hours for module | 200 |
Method | Percentage |
Written exam | 50 |
Written assignment including essay | 50 |
Summative assessment- Examinations:
2 hours closed book written examination
Summative assessment- Coursework and in-class tests:
The written assignment is an individual project set week 2 of Spring Term, due end of week 1 of Summer term.
Formative assessment methods:
Penalties for late submission:
The below information applies to students on taught programmes except those on Postgraduate Flexible programmes. Penalties for late submission, and the associated procedures, which apply to Postgraduate Flexible programmes are specified in the policy £Penalties for late submission for Postgraduate Flexible programmes£, which can be found here: