Module code: PHY3048

Module provider


Module Leader

ADAMS JM Dr (Physics)

Number of Credits


ECT Credits



FHEQ Level 6

JACs code


Module cap (Maximum number of students)


Module Availability

Semester 2

Overall student workload

Independent Study Hours: 117

Lecture Hours: 33

Assessment pattern

Assessment type Unit of assessment Weighting
Examination EXAMINATION - 1.5 HOURS 70%
Coursework COURSEWORK 30%

Alternative Assessment

Alternative assessment: None

Prerequisites / Co-requisites


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 aims

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

Learning outcomes

Attributes Developed
Understand the mathematics and models that underpin the analysis of financial data, including the properties of random variables, probability distributions (including the Levy distribution) and share price models and be able to assess their validity and remit;
Know about a range of common financial derivatives, be able to explain financial terminology and produce pay-off and profit diagrams for forward contracts, put and call options;
Understand and be able to derive and use the Black-Scholes-Merton equation and be able to determine the prices of European options through its solution or through binomial models;
Examine and explain the role of quantities known as the “greeks” in financial analysis.

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

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, Stochasti

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



Portfolio optimisation theory.


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


Assessment Strategy

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

Understanding of the concepts of derivative pricing.


Thus, the summative assessment for this module consists of:

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


Formative assessment

Many problem sets are issued during the course, and feedback will be given during tutorial sessions.




Reading list


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 2017/8 academic year.