FINANCIAL DERIVATIVES - 2019/0

Module Overview

This module covers various different descriptions of diffusion, and the application of statistical physics to model share prices. This mathematics is then applied to calculating prices for some vanilla financial derivatives, followed by some exotic derivatives.

Module provider

Physics

Module Leader

SWEENEY Stephen (Physics)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 6

Module cap (Maximum number of students): N/A

Module Availability

Semester 2

Prerequisites / Co-requisites

None.

Module content

Indicative content includes:

 

Financial products and markets: Cash, interest rates, Stocks, dividends, Bonds, Credit Default

Swaps, Commodities, Derivatives, Markets, participants, Bid-Offer spread, Kelly Criterion, Arbitrage.

 

Stochastic Processes: Random Variables, Probabilities, Variance, Correlation, Central limit theorem, Normal distribution, Fat tails, Brownian motion, Langevin equation, Diffusion, Stochastic

Processes, Wiener process, Ito Calculus, Fokker-Planck equation.

 

Option Pricing: Binomial trees, Share price models, drift and volatility, Forward contracts, European and American options, Calls and Puts, Binomial pricing model.

 

Option Pricing: Continuous time, Black-Scholes model, Greeks, Discrete delta hedging, Implied volatility, volatility smiles.

 

Barrier options: Diffusion with absorbing barrier, knock-out and knock-in options, hedging in practice.

 

Portfolio optimisation theory.

 

Assessment pattern

Alternative Assessment

Alternative assessment: None

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate:

• Understanding of the concepts of derivative pricing, and underlying mathematics.

• coursework assignment involving data analysis and computational modelling of financial instruments, and a final examination of 1.5h duration in which 2 questions from 3 must be answered.

Module aims

• The aims are to expose the students to the fundamentals of financial derivatives, to explore their underlying science by analogy to physical systems, and to show, by various methods, how the fair price of financial options may be determined.

Learning outcomes

Methods of Teaching / Learning

The learning and teaching strategy is designed to:

Help students develop an understanding of how the ideas of Brownian processes can be applied to financial derivatives.

 

The learning and teaching methods include:

33 hours of lecture classes/tutorials and computer-based problem-solving

 

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: PHY3048

Programmes this module appears in

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2019/0 academic year.