Mathematical Trading and Finance MSc

at City University of London

Structure
 

What will you learn

• You will have learned a good understanding of the technical aspects used in financial
  markets, starting from the financial theory, looking at different financial instruments and showing various applications of the theoretical concepts.

• You will gain a good understanding of stochastic modelling, mathematical finance and econometrics as well as programming.

• You will also obtain a very good understanding of different financial assets, in particular derivatives, and how they can be used in different context, such as risk management, asset management or structuring.

• The MSc Mathematical Trading and Finance programme will also help you to understand the financial theory used in financial markets with an emphasis on practical applications.

• You will have three different possibilities to complete your degree in the third term, including writing a dissertation or an applied project , or you can also opt to get all the credits through taught electives.
   

Induction weeks

All of our MSc courses start with two compulsory induction weeks which include relevant refresher courses, an introduction to the careers services and the annual careers fair.

Term 1

• 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.
   

• Derivatives

  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

  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

  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

  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.
   

Term 2

• Fixed Income

  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

  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.
   

• 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.
   

• 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.
   

Term 3

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 offered in 2021

• 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.

• A UK upper second class degree or above, or the equivalent from an overseas institution.

• Your academic background should be in a highly quantitative subject such as mathematics, physics, engineering, economics or computer science and having covered areas such as statistics, linear algebra and calculus.

• Work experience is not a requirement for this course.
   

Course Syllabus

You may be requested to provide a syllabus of specific modules undertaken during your studies as part of the assessment process. This is not required at the point of submitting an application and will be requested directly by the admissions team only if required as part of the assessment.
 

If you have been studying in the UK for the last three years it is unlikely that you will have to take the test.

If you have studied a 2+2 degree with just two years in the UK you will be required to provide IELTS results and possibly to resit the tests to meet our requirements.
 

IELTS

• The required IELTS level is an average of 7.0 with a minimum of 6.5 in the writing section and no less than 6.0 in any other section.

Fees

UK/EU/International
£29,500
Tuition fees are subject to annual change
Fees in each subsequent year of study (where applicable) will be subject to an annual increase of 2%. We will confirm any change to the annual tuition fee to you in writing prior to you commencing each subsequent year of study (where applicable).
 

Deposit: £2,000 (usually paid within 1 month of receiving offer and non-refundable unless conditions of offer are not met)
 

First installment: Half fees less deposit (payable during on-line registration which should be completed at least 5 days before the start of the Induction period)
Second installment: Half fees (paid in January following start of course)

Career pathways

The job opportunities for students from the three quants master's programmes are very similar. They usually find employment with large investment banks, but also some smaller boutique finance firms, hedge funds or other specialist companies.

Working as quantitative analysts, in risk management, on fixed income security desks or in the asset management industry including hedge funds are typical jobs for students from the MSc Mathematical Trading and Finance degree.

Some students also secure positions on trading desks. Hear from our Mathematical Trading and Finance alumni, what they learnt at Bayes and where they have gone on to work.

You will also have the skills to study for a PhD in the area of quantitative finance and financial markets.
 

Class of 2020 profile

Recent graduate of the MSc in Mathematical Trading and Finance programme have secured positions in companies including:

• Research Analyst - Ambrosia Capital

• Equity Index Intern - Equity Operations - Solactive AG

• Investment Banking Associate - GF Securities

• Equity Research Analyst - Fiansia Syrus Securities.