Aims

To develop a knowledge and understanding of some commonly used financial models in the analysis of financial data.

Module summary

The demand for mathematical skills in financial institutions has increased considerably over the recent past. Financial analysts use sophisticated stochastic models to describe the unpredictable behaviour of markets, derive computable pricing methods and analyse financial data. The course deals with commonly used models for stock prices of risky assets and methods for pricing financial derivatives, such as options and contingent claims. The analysis of such models requires knowledge from probability, stochastic processes and statistics.

Outline Of Syllabus

Risk-free money market. Financial derivatives: call and put options of European type, contingent claims, other exotic options, arbitrage. Continuous-time models of stock price: Brownian/Geometric Brownian motion, Black-Scholes pricing. Volatility estimation using historic data, implied volatility. Monte Carlo pricing. Itô calculus: Itô integral and Itô formula. Models of interest rate as stochastic differential equations. Use of R for calculation and simulation.

Teaching Rationale And Relationship

Lectures are used for the delivery of theory and explanation of methods, illustrated with examples, and for giving general feedback on marked work. Problem Classes are used to help develop the students’ abilities at applying the theory to solving problems.

Assessment Rationale And Relationship

A substantial formal unseen examination is appropriate for the assessment of the material in this module. The coursework assignments allow the students to develop their problem solving techniques, to practise the methods learnt in the module, to assess their progress and to receive feedback; these assessments have a secondary formative purpose as well as their primary summative purpose.

In the event of on-campus examinations not being possible, an on-line alternative assessment will be used for written examination 1.