Quantitative Finance MSc

• Asset Pricing

  This module focuses on the introduction of pricing financial securities, which forms the basis for understanding asset pricing behaviour and the cornerstone of many asset pricing models. The focus is on spot securities, mainly equities and debt instruments.

  The module also introduces students to the fundamental theory used by practitioners and academics in the wider field of finance, in particular asset management. That includes portfolio theory, the CAPM, factor models and measuring risk and return.

  Those concepts are widely used by financial market participants. At the end of this module the various building blocks are being put together in the discussion of performance and persistence of performance of mutual funds.

  Module Leader in 2023-24: Dr Dirk Nitzsche

• Derivatives

  This module introduces to derivatives instruments and derivatives markets in the context of financial risk management. Focus is specifically given to the identification of the risks inherent in derivative securities.

  On completion of this module, students will be able to undertake quantitative applications of concepts in a practical setting and understand the contribution of derivative securities to a sensible risk management practice.

  Module Leader in 2023-24: Prof. Keith Cuthbertson

• Foundations of Econometrics

  The course provides the essential statistical and econometric techniques needed to conduct quantitative research in finance and economics.

  This combination of econometric theory and application will enable students to understand and interpret empirical findings in a range of financial markets, including reading of empirical academic literature and critical assessment econometric applications undertaken by industry practitioners.

  Module Leader in 2023-24: Prof. Giovanni Urga

• Stochastic Modelling Methods in Finance

  The module provides the necessary mathematical tools on which the entire programme is based. Specifically, the module offers a rigorous introduction to Brownian motions and stochastic calculus.

  Furthermore, the module focuses on the construction of the mathematical framework on which Mathematical Finance is based, starting from the no-arbitrage principle, all the way to its mathematical formulation using martingales and martingale measures.

  These concepts will then be applied in Finance for pricing and hedging books of derivative contracts.

  Module Leader in 2023-24: Prof. Laura Ballotta

• Programming for Quants – Python and Matlab

  Strong research skills are a key element of development strategy for companies and institutions large and small. In particular the ability to programme and to automate procedures. This module focuses on Python programming in term 1 and introduces Matlab in term 2.  The teaching covers syntax and basic concepts used in finance and introduces a number of financial applications.

  The teaching focuses on the main programming skills used in the financial industry.  That includes operating on matrices, using loops, working with conditional statements, subroutine/functions/procedures, graphics, data handling and optimisations.

• Fixed Income

  The module provides a thorough introduction to the market of fixed income securities, such as bonds, swaps and interest rate options.

  Futrthermore, the module covers the main modelling streams in fixed income securities. It also offers insights in the most recent issues that affected the fixed income market, such as multicurve rates, negative rates and counterparty credit risk.

  Module Leader in 2023-24: Prof. Gianluca Fusai

• Risk Analysis

  Financial debacles are a constant reminder of the relationship between financial risk and reward. The quantitative approach to this relationship is ever more dominant in the market and subject to constant innovation.

  As market participants need to keep abreast of new developments, the Risk Analysis module provides a good path of study in this field.

  The aim of this module is to help you develop a solid background for evaluating, managing and researching financial risk. To this end you will learn to analyse and quantify risk according to current best practice in the markets.

  Module Leader in 2023-24: Prof. Gianluca Fusai

• Econometrics of Financial Markets

  Econometrics is an essential tool for the empirical analyses of financial markets as well as the development of quantitative strategies for forecasting, pricing and risk management analyses in financial markets.

  A good understanding of the developments in financial econometrics is of great relevance to the analysis of financial markets, building both technical skills and the ability to carry out advanced empirical research.

  Module Leader in 2023-24: Prof. Giovanni Urga

• Numerical Methods - Applications

  This module introduces basic concepts used in numerical methods as well as graphical techniques often used to visualise relevant data.

  The module also aims to introduce the concepts used in derivatives pricing and present Monte Carlo simulation methods in finance.

  Additionally, this module aims to transmit an appreciation of performance criteria, their formulation and application in this area.

  Module Leader in 2023-24: Dr Ioannis Kyriakou

You will be able to tailor your degree in the third term by choosing electives to complete your education. Alongside electives you may also choose a Masters dissertation or an applied research project.

You may choose from the following three options in your final term.

• Option 1: Students can take five specialist elective modules (5 x 10 credits).
• Option 2: Students can opt to write a 10,000 word Business Research Project (40 credits) and take one specialist elective module (1 x 10 credits).
• Option 3: Students can opt to write a 3,000-5,000 word Applied Research Project (20 credits) and take three specialist elective modules (3 x 10 credits)

Projects

• Business Research Project

  It is important for aspiring professionals to demonstrate, on an individual basis, their ability to apply concepts and techniques they have learned in an in-depth study of a topic of their choice and to organise their findings in a report, all conducted within a given time limit.

  Therefore, this module aims to train you to undertake individual research and provide you with an opportunity to specialise in a contemporary business or finance topic related to your future career aspirations.

  You are required to submit a project of approximately 10,000 words on any subject area covered in the rest of the programme.

  Topics covered in recent years are hedging climate change with weather derivatives, deep learning techniques for rough volatility models, multivariate Realised Volatility models and variance risk premia in commodity markets..

• Applied Research Project

  The aim of this module is to enable you to demonstrate how to integrate your learning in core and elective modules and then apply this to the formulation and completion of an applied research project.

  You will be required to demonstrate the skills and knowledge that you have acquired throughout your MSc study.

  You will undertake a short piece of applied research on a question of academic and/or practical relevance. Guidelines will be provided in order to help you identify the research question.

  Based on your chosen topic, you must write a report of around 4,000 words that summarises and critically evaluates your method and your findings.

Electives offered in 2023

• Applied Machine Learning
• Emerging Global Risks
• Ethics, Society and the Finance Sector
• Hedge Funds
• Investment Strategy
• Technical Analysis and Trading Systems
• Trading and Hedging in the Forex Market
• VBA with Application for Finance.

International electives

• FinTech (taught in Italy)
• Investment Strategy (taught in New York, USA).

*Please note that electives are subject to change and availability.