Derivatives and risk management

Course	T-814-DERI
Semester	20241
ETCS	8
Core	Yes

Year	1. year
Semester	Spring 2024
Level of course	5. Second cycle, intermediate
Type of course	Core
Prerequisites	No prerequisites.
Schedule	Taught for 12 weeks.
Lecturer	Ralph Rudd
Content
The core focus of this course is study and use of quantitative techniques in risk management. The approach is centered around the study of portfolio value change, where we consider general portfolios that can consist of a mixture of equity, fixed income, credit, and derivative instruments. The risk of a portfolio is represented by its loss distribution, which is a function of its risk factors. In this course we examine how to model and manipulate this loss distribution. The modelling proceeds via modelling the risk factors themselves, and we investigate the properties of common risk factors in the real world. The manipulation of the loss distribution is done by modifying the portfolio constituents, usually through hedging. To assess the risk of a portfolio, we look at summary measures of its loss distribution, primarily value-at-risk and expected shortfall. We examine the properties of these risk measures and investigate their shortcomings.
Learning outcome - Objectives
After completing this course, students will have a good knowledge of how to identify, quantify and manage derivative and market risk. The learning outcome can be broken down into the following sub-outcomes: Be able to define and explain the fundamental concepts used in the measurement and management of financial risk. Be able to analyse and model changes in portfolio value and derive loss distributions. Apply the loss distribution framework to different kinds of asset and liability portfolios. Apply different quantitative approaches to measuring risk, with particular focus on risk measures that are calculated from loss distributions, like value-at-risk and expected shortfall. Be able to price various derivatives contracts, such as options, futures and swaps, from a risk neutralising perspective Be able to build realistic models for risk management purposes by considering the empirical properties of fundamental risk factors and developing models that share these properties. To model multivariate loss distributions with complex cross-dependencies. Be able to aggregate and disaggregate risk across multi-instrument portfolios.
Course assessment
Assessment consists of theoretical and computational exams.
Reading material
No reading material found.
Teaching and learning activities
In-person, interactive lectures.
Language of instruction	English