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The award
MSc

How long you will study
12 months

Domestic course fees
GBP 25000 per year

How you will study
full-time

Course starts
September

International course fees
find out

All study options

About Financial Mathematics at City, University of London

Overview

Who is it for?

To successfully complete this course, you must have a very good understanding of mathematics. You may well have studied maths, physics or engineering degrees as an undergraduate.

Or you might have a bachelor's degree in economics or science and in particular computer science, which, coupled with your interest in stochastics, could also qualify you for this programme.

You should have a general interest in learning the more technical and mathematical techniques used in financial markets; but you don't need to have a background in finance.

Objectives

The MSc Financial Mathematics focuses on stochastics and simulation techniques, but also covers some econometrics. You'll study core modules covering asset pricing, risk management and an introduction to key financial securities such as equities, fixed income and derivatives.

You'll cover a wide range of elementary and advanced topics in stochastics, including Levy processes and different simulation techniques. You'll be taught Matlab and VBA and you have the opportunity to learn other programming languages as part of our electives offering, such as Python or C++.

There are three ways to complete the third term. Either you'll choose five electives from around 40 optional modules in your final term. Or you can choose to complete a traditional dissertation, known as a 'business research project', which counts for four electives, or a shorter 'applied research project', which is the equivalent of two elective modules.

Structure

  • You will have gained a very good understanding of the technical aspects used in financial markets, including wide ranging financial theory and different financial assets.
  • You will gain a good understanding of stochastic and mathematical finance and gained some knowledge of econometrics and forecasting. You will also have obtained a good understanding of programming, in particular Matlab.
  • From the MSc Financial Mathematics you will also understand how the theory is being applied in the financial industry and what practical issues are.
  • In the third term you have three different options how you can complete your MSc, including a project or choosing only electives. Popular electives include Modelling and Data Analysis, Advanced Financial Engineering and Credit Derivatives, Credit Risk Management, Quantitative Risk Management. Introduction to Python.

Term 1

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
    • 3 x 3 hour lectures over the ten week term
    • 52 hours self directed study over the ten week term

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 MATLAB and VBA as a programming language. The module introduces the main programming skills which are helpful in the financial industry. Operating on matrices or arrays, loops, subroutine and optimisations are core skills which are being introduced in this module.

Term 2

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.

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.

See the MSc in Financial Mathematics programme specification.

Assessment methodsTerm datesAssessment methods

Assessment methods

Assessment

We review all our courses regularly to keep them up-to-date on issues of both theory and practice.

To satisfy the requirements of the degree course students must complete:

  • nine core courses (Eight at 15 credits each, one at 10 credits)

and either

  • five electives (10 credits each)
  • three electives (10 credits each) and an Applied Research Project (20 credits)
  • one elective (10 credits) and a Business Research Project (40 credits)

Assessment of modules on the MSc in Financial Mathematics, in most cases, is by means of coursework and unseen examination. Coursework may consist of standard essays, individual and group presentations, group reports, classwork, unseen tests and problem sets. Please note that any group work may include an element of peer assessment.

Two Induction Weeks

The Financial Mathematics course starts with two compulsory induction weeks, focused on:

  • an introduction to careers in finance and the opportunity to speak to representatives from over 75 companies during a number of different industry specific fairs.
  • a reminder course of advanced financial mathematics, statistics and basic computing which forms a prerequisite of the core modules in term 1.
Term dates

Term dates

Term dates 2018/19

In-Person ID-Checks (all students must attend): Commences 17 September 2018

Compulsory Induction: 18 - 29 September 2018

Term I
1 October 2018 - 7 December 2018
Term I exams
7 January 2019 - 18 January 2019

Term II
21 January 2019 - 29 March 2019
Term II exams
22 April 2019 - 3 May 2019

Term III
6 May 2019 - 28 June 2019
Term III exams
1 July 2019 - 12 July 2019

Resit period
Students who are required to resit an examination or invigilated test  will do so in the period:
12 - 30 August 2019

Submission deadline for Business Research Project or Applied Research Project 
1 September 2019

Official Course End Date
30 September 2019

Application

How to apply

Documents required for decision-making

  • Transcript/interim transcript
  • Current module list if still studying
  • CV
  • Personal statement (500-600 words)

Documents which may follow at a later date

  • IELTS result
  • Confirmation of professional qualification examinations/exemptions/passes, if applicable
  • Two references
  • Work experience is not a requirement of this course
  • For a successful application to receive an unconditional status all documents must be verified, so an original or certified copy of the degree transcript must be sent by post to Specialist Masters Programme Office, 106 Bunhill Row, London, EC1Y 8TZ, UK

We cannot comment on individual eligibility before you apply and we can only process your application once it is fully complete, with all requested information received.

Individual Appointments

If you would like to visit us to discuss your application please do arrange an individual appointment.

Entry requirementsEnglish language requirementsEntry requirements

Entry requirements

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.

English language requirements

English language requirements

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.

Read more

Please note that due to changes in the UKVI's list of SELTs we are no longer able to accept TOEFL as evidence of English language for students who require a CAS as of April 2014.

Career pathways

The job opportunities for students from the three quants Masters programmes are very similar and students usually find employment with either large investment banks, or smaller specialist companies or financial boutique firms. Working as a quantitative analysts using stochastic, technical risk management position, pricing fixed income securities and structuring are some of the positions Financial Mathematics students are well qualified for. You will also have the skills to study for a PhD in the area of quantitative finance and financial markets.

Study options for this course

Notes about fees for this course

UK/EU/International

£25,000 Tuition fees are subject to annual change

Fees in each subsequent year of study (where applicable) will be subject to an annual increase limited by the All Items Retail Prices Index. 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 (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 in-person ID–checks)
Second installment: Half fees (paid in January following start of course)

Information about Scholarships

Entry requirements

Contact City, University of London to find course entry requirements.

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