Course description
MSc Quantitative Finance and Financial Engineering – Course structure
All taught course units are 15 credits.
Semester 1
• Foundation of Finance Theory
This course provides a foundation in the most important models in finance: general noarbitrage
relationships (forward parity, put-call parity, MM theorem, the law of one price),
stock valuation models (APT, CAPM, TSP) and option pricing models.
• Stochastic Calculus
The course content includes: Wiener process; continuous local martingales; the quadratic
variation process; Ito’s integral with respect to a continuous semi-martingale; the Levy
characterisation theorem; the martingale representation theorem; optimal prediction of the
maximum process; Bassel process; the Ornstein-Uhlenbeck process; branching diffusion;
Brownian bridge; the Shiryaev process; the sequential testing equation; the quickest detection
equation; the existence and uniqueness of solutions in the case of Lipschitz coefficients.
• VBA/C++ with Finance Applications*
This course covers Microsoft's Visual Basic (VBA) language in conjunction with Excel's user
interface and its formulas and calculation capabilities, to deliver a powerful and flexible trading
tool. The coverage on C++ is introductory and does not assume prior knowledge of
programming. You learn how to incorporate C++ modules into Excel through the dynamic
linked library. All example programmes are based on finance applications.
• Derivative Securities*
This course covers the valuation and application of financial derivatives instruments, and the
use of no-arbitrage arguments and risk neutral valuation for the relative pricing of financial
derivatives.
* If you can produce a transcript that shows you have studied option pricing and/or VBA/C++
programming previously, you may apply to the course director/coordinator to swap these
modules for one or more of the following modules:
• International Macroeconomics and Global Capital Markets
This course examines major issues in the macroeconomic relations between countries.
These include: evidence of globalisation in capital markets from parity conditions; the intertemporal
approach to current account dynamics; the fundamental determinants of the real
exchange rate; the sustainability of current account deficits, with special reference to the US
experience; capital account liberalisation; alternative measures of international capital
mobility, and the Feldstein-Horioka puzzle; economic growth, theory and policy.
• Martingales with Applications to Finance
The course content includes: probability, measures and random variables; integration with
respect to a probability measure; price processes, self-financing portfolios and value
processes; arbitrage opportunities and equivalent martingale measures; market
completeness; options and option pricing; stopping times and the optional sampling theorem.
• Portfolio Investment
This course provides an advanced coverage of the main principles of investment analysis and
portfolio management; it examines the steps involved in constructing an investor’s optimal
portfolio, how to revise this portfolio to ensure it remains optimal, and how to measure the
performance of this portfolio.
Semester 2
• Financial Econometrics
This course covers OLS, ML and GMM estimation methods, univariate time series analysis
and various topical issues such as ARCH, Vector Autoregressive Models, unit roots, error
correction, co-integration and non-linear time series models.
• Interest Rate Derivatives
This course unit provides you with foundations of interest rate models and the conceptual
framework for valuing interest rate derivatives. The unit covers interest rates and bond
prices, single period and multiperiod interest rates instruments, interest rate derivatives,
interest rate models, spot rate models and forward models.
Two course units from:
• Computational Finance
This course covers computational methods, including Monte Carlo and Lattice methods for
option pricing, finite difference methods for parabolic PDEs with emphasis on Crank Nicolson
methods for parabolic systems, point and line relaxation and PSOR methods, and quadrature
methods.
• Mathematical Modelling of Finance
The course content includes: no-arbitrage valuation of options and futures; models for the
movements of stock prices, Brownian motion and geometric Brownian motion; stochastic and
deterministic processes; basics of stochastic calculus and Ito's lemma; derivation of the
Black–Scholes PDE and the assumptions behind it; formulating the mathematical problem,
determining boundary conditions and deriving the solution of the heat conduction equation
using the Dirac delta function; extension to assets paying dividends, early exercise and free
boundary problems.
• Real Options in Corporate Finance
This course evaluates strategy and management value in property, power, resources, R&D,
football, dot.coms, telcos, banking and consulting. The course surveys the real options that
practitioners have identified in these industries.
• Credit Risk Modelling
This course unit provides students with advanced approaches to quantitative credit risk
modeling and management in the context of the Basel II and Solvency II regulatory
framework.
Research dissertation (60 credits)
You carry out an original piece of research on a subject relating to the course. Our MSc
dissertation topics align with the research interests of leading financial institutions from
the City of London and internationally. Senior members of these organisations propose
several of the dissertation topics, which, subject to approval, members of academic staff
supervise. Successful completion can require consultations with officers of the financial
institution, leading to a final presentation of findings.
