Mathematical Trading and Finance

• 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 2022-23: 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 2022-23: 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 2022-23: 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 2022-23: Prof. Laura Ballotta

• Applied Research Tools

  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 as a programming language and students will learn the basics in term 1 with some applications to finance being introduced in term 2.

  The module introduces the main programming skills which are helpful in the financial industry. Operating on matrices, loops, conditional statements, subroutine/functions/procedures and optimisations are core skills which are being introduced in this module.

• 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 2022-23: 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 2022-23: Prof. Gianluca Fusai

• Quantitative Trading

  This trading focused module introduces students to the world of computer-based trading and dealing with high frequency data.

  Some relevant market microstructure concepts, such as bid-ask spreads, liquidity and other concepts are being introduced before the focus moves to high frequency trading strategies and other automated trading concepts.

  Module Leader in 2022-23: Dr Bernd Hanke

• Machine Learning

  This module provides on overview of machine learning concepts, techniques and algorithms used in practice to describe and analyse complex data and design predictive analytics methods. You should expect to engage with the main idea and intuition behind modern machine learning tools from a practical perspective.

  Standard computing skills in R, Python and Matlab will be used to put in practice the theory discussed during the lectures.

  Module Leader in 2022-23: Dr Rui Zhu

You will be able to tailor your degree in the third term by choosing to complete your education with either a business research project or an applied research project, or solely through electives.

You may choose from the 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.

  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 construction of optimised equity and crypto portfolios, impact of social media sentiment on portfolio allocation, and quantification of the performance of global minimum variance portfolios.

• 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 3,000–5,000 words that summarises and critically evaluates your method and your findings.

Electives offered in 2022

• Emerging Global Risks
• Advanced Financial Modelling and Forecasting
• Behavioural Finance
• Ethics, Society and the Finance Sector
• Financial Crime
• Hedge Funds
• Technical Analysis and Trading Systems
• Trading and Hedging in the Forex Market
• Trading and Market Microstructure
• VBA with Application for Finance.

International electives

• FinTech (taught in Italy)

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

See the MSc in Mathematical Trading and Finance programme specification.