This module aims to equip students with the core mathematical and computational methods required for the pricing, hedging, and risk management of financial derivatives, while developing students’ capacity to translate finance theory into practical, industry-relevant financial analysis. It contributes to a rigorous understanding of how probability, stochastic calculus, and diffusion processes underpin modern asset and option pricing frameworks, enabling students to move confidently between theoretical derivation and empirical application. Through a learning experience combining empirical project work with AI-assisted role-play simulation, students can develop the analytical judgement, quantitative modelling skills, and professional communication competencies essential for advanced study and professional practice in quantitative finance.
A Understand the main principles of financial markets, major asset classes, and classical asset pricing models B Understand and analyse the use of financial derivatives and hedging strategies; Be able to price and analyse forwards, futures, options, and options strategies C Understand, implement, and analyse the binomial tree model D Understand, analyse, and use probability distributions in option pricing applications E Understand and utilize diffusion processes and stochastic calculus such as Ito’s Lemma in the Black-Scholes framework
This module will be repeated over two semesters. In semester 1, the module will be delivered for