The University of Edinburgh and
Markets, 15 hours. The subject of derivatives is one that
lies at the heart of the MSc. This half module will introduce students
to the traded and over-the-counter derivatives markets. The main
derivatives contracts will be described, and there will be discussion
of the various practical issues connected with investment in the
processes I, 35 hours. The mathematics needed in financial
modelling is that of stochastic processes. This module will treat
discrete stochastic processes, introducing simple financial models and
showing how to price financial products in the discrete setting. It
will also introduce Brownian motion and Stochastic
Management, 30 hours. Credit risk is one of the key areas in
modern financial mathematics. This module will introduce students to
quantitative models for measuring and managing credit risk. It also
aims to provide students with an understanding of the credit risk
methodology used in the financial industry and the regulatory framework
in which the credit risk models operate.
Management, 30 hours. This module will give students an
introduction to the process of modelling financial risk based on the
rigorous analysis of historical data. The course will look at a variety
of tools to tackle problems involving financial data. Essential
elements of the learning process are the computer labs where classroom
theory is turned into practice.
methods, 30 hours. Financial time series arise from
stochastic processes. When it comes to the implementation of models it
is essential to understand statistical techniques to estimate
parameters and to fit models to real data. This module will cover a
variety of statistical models as well as the concepts of estimation and
Simulation, 10 hours. There are many financial models where analytical solutions for derivative prices cannot be obtained. In these cases the only way to make progress is via simulation. This module will explain the basic ideas and methods of the simulation of behaviour of financial systems.
processes II, 15 hours. Stochastic Processes II will
develop in detail the topic of stochastic calculus
introduced in Stochastic Processes I, the key tool for the analysis of
the continuous-time stochastic process framework in which financial
models are set.
Modern portfolio theory, 30 hours. This module will allow students to understand the theory of preference using utility theory and how this can be applied to selecting optimal portfolios. It will show how portfolio selection models can be extended to become pricing models and then focus on the basics of the CAPM and APT pricing models.
pricing and financial modelling, 30 hours. The trade in
derivatives has become much greater than trade in the underlying
assets. This module will build on the stochastic processes courses to
actually price and hedge a large number of financial products. It will
deal with the plain vanilla options which fit into the Black-Scholes
picture and then extend this to interest rate models and what happens
when the Black-Scholes model breaks down.
Time series analysis, 15 hours. This half-module will introduce students to the main concepts underlying the analysis of time series, and will discuss in detail some models which are frequently used for financial time series.
Financial econometrics, 15 hours. Financial econometrics is the statistical modelling of financial data such as asset prices and returns. This module will begin with the analysis of univariate time series and then introduce the essentially econometric material in the context of multivariate financial time series.
techniques for partial differential equations, 15 hours.
Financial pricing problems can often be reduced to solving a partial
differential equation. In this module numerical techniques for the
solution of such equations will be introduced.
Mathematical programming, 15 hours. Optimization techniques are used in many areas of finance. This module will discuss some of the theory and the practical implementation, introducing dynamic programming ideas.