Financial Mathematics

Core modules:

• Asset Pricing

  • 15 credits
  • 3 hours per week in lectures
  • 12 hours per week self directed study

  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.

• Derivatives

  • 15 credits
  • 3 hours per week in lectures
  • 12 hours per week self directed study

  To introduce derivatives and derivative models in the context of financial risk management. To complement general finance courses with specific instruction in the key derivatives area.

  To enable you to use models in this area in practical applications. To transmit to you the fundamental mathematical modelling techniques underpinning the subject.

• Foundations of Econometrics

  • 15 credits
  • 3 hours per week in lectures
  • 12 hours per week self directed study

  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 you 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.

• Stochastic Modelling Methods in Finance

  • 15 credits
  • 3 hours per week in lectures
  • 12 hours per week self directed study

  The module provides the necessary mathematical tools on which the entire programme is based.

  • To introduce you to Brownian motion and stochastic calculus
  • To provide examples of applications of stochastic calculus in financial areas
  • To provide the tools required for a rigorous understanding of financial modelling and pricing techniques
  • To learn fundamental numerical methods for simulating trajectories of commonly used stochastic processes.

• Applied Research Tools

  • 10 credits
  • 8 x 3 hour lectures over the ten week term
  • 52 hours per week self directed study

  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.

Core modules:

• Fixed Income

  • 15 credits
  • 3 hours per week in lectures
  • 12 hours per week self directed study

  To provide a foundation in a crucial area of financial markets and quantitative finance. To complement the general derivatives course with specific instruction in a key derivatives area.

  To acquaint you with the main modelling streams in fixed income securities. To enable you to use models in this area in practical applications. To transmit to you the fundamental mathematical modelling techniques underpinning the subject.

• Risk Analysis

  • 15 credits
  • 3 hours per week in lectures
  • 12 hours per week self directed study

  Financial disasters 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.

• Advanced Stochastic Modelling

  • 15 credits
  • 3 hours per week in lectures
  • 12 hours per week self directed study

  The module introduces more recent developments in the field of financial mathematics to:

  • Introduce you to more recent advances in mathematical finance
  • Provide you with the mathematical tools required for the setting up of more sophisticated financial models and valuation framework
  • Introduce you to pricing frameworks that go beyond the Black-Scholes model and the necessary numerical methods.

• Simulations Techniques and Financial Modelling

  • 15 credits
  • 3 hours per week in lectures
  • 12 hours per week self directed study

  This module focuses on applications of numerical methods and programming languages to finance. Students will learn Monte Carlo Simulations; Tree-based pricing methods; Fourier inversion based methods; Applications in Risk Management.

  This module integrates the programming language Matlab and is partly lab based.

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.

  Typical projects can involve any of the following: extracting data from electronic databases or by hand; statistical analysis of large or small populations; interviews; case studies of an industry or a sector or of a business / finance issue in a particular country setting.

• 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 planned to run in 2021

• Advanced Financial Engineering and Credit  Derivatives
• Credit Risk Management
• An Introduction to Machine Learning
• Introduction to Copula Modelling
• Introduction to Python
• Operational Risk Management
• Trading and Hedging in the Forex Market
• Trading and Market Microstructure
• Ethics, Society and the Finance Sector

International elective

• Introduction to FinTech (taught in Italy)

See the MSc in Financial Mathematics programme specification.