Financial Mathematics MSc/PGDip | Middlesex University London
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Financial Mathematics MSc/PGDip

Learn about the course below
Code
PGG1N3
Start
October 2018
September 2017 (EU/INT induction)
Duration
1 year full-time
2 years part-time
Attendance
Full-time
Part-time
Fees
£8,800 (UK/EU)
£13,500 (INT)
Course leader
Zainab Kazim Ali

A combination of mathematics, statistics and computing, financial mathematics is a specialism vital to the day-to-day functioning of the world's economic institutions. Highly technical and theoretical aspects of mathematics take on a practical importance which can affect millions of lives through this fascinating discipline, which involves predicting the behaviour of markets and suggesting strategies for investment.

Why study MSc Financial Mathematics at Middlesex University?

We believe strongly that the work you do must be relevant to the world of work – that's why our course has a strong practical slant. It also has the unusual and significant advantage of including from-scratch training in computer programming, allowing you to develop first-class computing skills alongside your mathematical expertise. You'll need a good degree in maths, or a related subject like physics or engineering, but no prior knowledge of finance.

Course highlights

  • Our course combines a comprehensive grounding in the theory of financial mathematics with thorough practical training
  • Our subscriptions to Bloomberg and Datastream allow you to work with real datasets
  • We'll teach you to code for financial mathematics in widely-used programming languages, without the need for prior experience
  • Guest lectures from industry specialists allow you to gain insights from practising professionals into real-life situations
  • The course is designed either for graduates considering a financial career, or for those already working in the industry looking for a greater understanding of finance and insurance risk
  • As a student of this course you'll receive a free electronic textbook for every module.

What will you study on the MSc Financial Mathematics?

You’ll develop an advanced understanding of the concepts and techniques of financial mathematics and statistics, and of how financial data is gathered and analysed. These will include probability; financial data and technical terms; options pricing and asset pricing; distributions; the future of prices and exchange rates; hedging investments; advanced stochastic analysis; mathematical modelling and analysis; portfolio management and selection; and research methods and techniques.

Through all this, you’ll develop the mathematical, financial and computational skills you need to make decisions; quantify and manage risks and balance risk with return; understand financial instruments; and evaluate and interpret financial data using programming and computer packages. You’ll also be able to source data from a range of different sources, including electronic databases.

There are five compulsory modules: portfolios and risk; probability and stochastic processes; risk measurement; financial data and computing; and pricing and stochastic calculus. You’ll then choose one further option from international risk management, time series and forecasting, and game and decision theories. At the end of the course you will submit a dissertation, which will allow you to gain in-depth knowledge of an area that interests you.

  • Modules

    • Risk Measurement (15 credits) - Compulsory

      The module aims to introduce students to concepts of risk measurement and analysis of financial data, and provides knowledge and basic skills required for risk measurement, technical analysis of financial data, investment decision-making, portfolio selection and optimisation.

    • Pricing and stochastic calculus (15 credits) - Compulsory

      This module aims to teach students to use pricing theory for derivatives, such as options, futures and forwards, using a risk-neutral probability and stochastic differential equations (SDEs), and explores discrete and continuous time models of stochastic processes with applications to pricing, such as the Black-Scholes equation for options pricing.

    • Portfolios and risk (30 credits) - Compulsory

      The module provides knowledge and basic skills required for financial product development, risk analysis, investment decision-making, portfolio selection and optimisation, as well as pricing of financial instruments.

    • Financial data and computing (15 credits) - Compulsory

      The module deals with information and communication technology to carry out financial market analysis in detail, and gives students the skills and ideas to implement computational approaches to financial problems.

    • Probability and stochastic processes (30 credits) - Compulsory

      This module aims to give students a solid grounding in some of the most important methods employed by statisticians by providing a deeper understanding of probability theory, inference theory and random processes.

    • Project (60 credits) - Compulsory

      The project allows students to consolidate their learning in a substantial piece of independent work utilising the skills and knowledge developed in the taught content.

    • International risk management (15 credits) - Optional

      This module aims to identify the major sources of risk involved in international economic and financial activity; develop the tools and techniques necessary to manage these risks and enable a critical appreciation of the interaction between corporate decision-making and capital market behaviour.

    • Time series and forecasting (15 credits) - Optional

      This module aims to build stochastic models for time series data sets, to understand or model the stochastic mechanism that gives rise to an observed series, and to predict or forecast the future values of a series.

    • Games and decisions (15 credits) - Optional

      This module gives students knowledge of the major concepts of decisions and game theories, and an understanding of the interrelation of these concepts, to determine the best strategy mathematically in order to optimize outcomes.

You can find more information about this course in the programme specification. Module and programme information is indicative and may be subject to change.

How will the MSc Financial Mathematics be taught?

Lectures and talks by visiting speakers will introduce you to concepts and techniques, which you’ll explore further through workshops, seminars, and presentations and discussions in class. Case studies will help you to relate theory to practice, and we’ll encourage you to think critically; some of your work will be done in groups. You’ll supplement all this with your own independent reading and study, including the use of online resources.

Assessment

You’ll be assessed through exams, tests and your dissertation, as well as other individual and group coursework

  1. UK & EU
  2. International
  3. How to apply
  1. UK & EU
  2. International

How can the MSc Financial Mathematics support your career?

A solid command of the principles and techniques of financial mathematics is essential for anyone working in trading, pricing, hedging, asset management, risk control and a variety of other areas of finance. There is currently a major drive to improve the mathematical abilities of staff working in financial institutions, and banks and companies which deal with risk are looking to hire employees with a solid mathematical background. This course will equip you for a wide range of careers in financial product development, risk analysis and management, pricing, investment decision making and portfolio development, with banks and financial companies or the government.

As well as in-depth knowledge of your subject, our course will provide you with many transferable skills. It will improve your research, data collection and interpretation, communication, presentation and teamwork skills, as well as your confidence and your ability to work under your own initiative and manage your own time.

Other courses

Applied Statistics MSc/PGDip

Start: October 2018, September 2018 (EU/INT induction)

Duration: 1 year full-time, 2 years part-time

Code: PGG311

Operational Research MSc/PGDip

Start: October 2018, September 2018 (EU/INT induction)

Duration: 1 year full-time, 2 years part-time

Code: PGG200

Financial Management MSc/PG Cert/PG Dip

Start: October 2018

Duration: 1 year full-time, 2 years part-time

Code: PGN399

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