Francesco Savarese studied on the MSc in Mathematical Trading and Finance at Bayes Business School. In this video he explains how Bayes is for the ambitious and helped him to achieve his career goal to become a trader.
Overview
Who is it for?
Want to develop innovative and effective trading strategies in the financial market with the help of advanced mathematical and statistical tools? Join the Mathematical Trading and Finance master’s to understand how to use your excellent applied mathematical skills in the world of finance.
You already have a general interest in the more quantitative and mathematical techniques used in financial markets, but you don’t need academic or work experience in finance. You’ll have good analytical skills and an interest in mathematics and statistics for this very rigorous academic course, as well as the equivalent of at least a UK upper second class degree in a highly quantitative subject such as mathematics, physics, engineering, economics or computer science, covering areas such as statistics, linear algebra and calculus.
I chose the MSc in Mathematical Trading and Finance at Bayes to merge my passion for the financial market with my interest to develop and strengthen my quantitative skills. Bayes helped me to build the foundations to get my first role, gaining an advantage when it came to quantitative and programming skills. This is especially true in the Fixed Income market, where quantitative skills are necessary to succeed.
Adriano Rosa
Objectives
In our postgraduate programme in Mathematical Trading and Finance, you’ll explore how financial innovation and globalisation have created new investment opportunities. Develop the quantitative skills and mathematical techniques used in financial markets, and learn how to develop algorithms for optimal investment decisions across various asset classes.
Core modules in quantitative trading and structuring differentiate this course from other quantitative finance courses. You’ll also focus on the theory of finance and different financial assets, exploring how these assets are priced and used for asset management or risk management purposes. You’ll build the mathematical and statistical skills needed in quantitative finance, including some stochastics. You’ll learn Python, and can choose to learn other programming languages, such as Matlab and VBA, as electives.
Term three offers you flexibility within your master’s: complete your postgraduate degree entirely by choosing electives, or undertake a business research or applied research project.
The difference between the MSc Mathematical Trading and Finance to the other two quants courses (MSc Financial Mathematics and MSc Quantitative Finance) are core modules which focus on quantitative trading and structuring.
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Structure
What will you learn
- Learn technical and practical skills useful for a career in front or middle office positions.
- Apply your new tools and knowledge in projects that put theory into practice.
- Benefit from our researchers’ expert experience in the financial sector and the knowledge they share in the classroom.
- Create a course to match your aims, with a range of electives and the choice of an applied research or business research project, or electives-only, in term three.
- Build your network of professional connections as you learn in the heart of the financial district, the City of London, surrounded by large and small financial organisations with strong links with Bayes.
The MSc Mathematical Trading and Finance programme will help you to understand the financial theory used in financial markets with an emphasis on practical applications. 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. - gain a good understanding of stochastic modelling, mathematical finance and econometrics as well as programming.
- 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.
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 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.
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 Mathematical Trading and Finance degree 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.
Term dates
Term dates 2023/24
- Induction: 11th September 2023 - 22nd September 2023
- Term one: 25th September 2023 - 8th December 2023
- Term one exams: 8th January 2024 - 19th January 2024
- Term two: 22nd January 2024 - 5th April 2024
- Term two exams: 22nd April 2024 - 3rd May 2024
- Term three - international electives: 6th May 2024 - 17th May 2024
- Term three: 20th May 2024 - 5th July 2024
- Term three exams: 8th July 2024 - 19th July 2024
- Resits: 12th August 2024 - 23rd August 2024
- Additional resit week - tests only: 26th August 2024 - 30th August 2024.
Timetables
Course timetables are normally available from July and can be accessed from our timetabling pages. These pages also provide timetables for the current academic year, though this information should be viewed as indicative and details may vary from year to year.
View academic timetables (add timetable and search for your programme)
Please note that all academic timetables are subject to change.
Teaching staff
Course Director
Senior Lecturer in Finance
The teaching staff on the MSc in Mathematical Trading & Finance have many years of practical experience working in the financial services sector and are also active researchers in their fields
This knowledge and experience inform the highly interactive lectures that make up the MSc in Mathematical Trading & Finance.
Module Leaders include:
Application
How to apply
Apply for MSc Mathematical Trading and Finance
Documents required for decision-making
- Transcript/interim transcript
- Grading system used by your university
- Current module list if still studying
- CV
- Personal statement - this should be 500-600 words in length and answer the following:
- Why have you selected this course? What are your motivating factors?
- What are your areas of interest within the course?
- What contributions do you feel you can make to the course?
- How do you see the course affecting your career plans?
Documents which may follow at a later date
- English language test result if applicable
- Confirmation of professional qualification examinations/exemptions/passes, if applicable
- Two references
- For a successful application to receive an unconditional status, all award documents must be verified, and should be provided to the relevant Admissions Officer via one of the methods stated in your offer.
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 arrange an individual appointment to discuss the application process and be given a tour of the facilities, please complete this form.
Please note - these are subject to availability.
Terms and conditions
Students applying to study at Bayes Business School are subject to City, University of London's terms and conditions.
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.
- 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.
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 an English language test.
If you have studied in the UK at degree level for less than three years (e.g. 3+1, 2+1, 2+2, etc.) you will be required to provide the results of an approved English language test and possibly resit the test to meet our academic entry requirements.
Full list of approved English language tests/qualifications and minimum requirements.
Fees
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
Our MSc in Mathematical Trading and Finance prepares you for success in the UK and around the world, in finance and related areas, within large investment banks, small specialist financial companies or boutique firms.
Your career path may take you into work as a quantitative, research or equity analyst, in risk management, on fixed income security desks, in the asset management industry including hedge funds, or into investment banking. You will also have the skills to study for a PhD in the area of quantitative finance and financial markets.
You’ll get support on identifying and achieving your goals from our careers team throughout your course, and benefit from our industry links and alumni network.
Hear from our Mathematical Trading and Finance alumni
Class profile
Recent graduate of the MSc in Mathematical Trading and Finance programme have secured positions in companies including:
- Analyst - Global Markets - BNP Paribas
- Financial Structuring - Dealing Room - National Bank of Greece
- FICC electronic trading sales - Global Markets - Credit Agricole
- Analyst - AIM Trade Desk - Bloomberg
- Intern - Equity Digital Market - J.P. Morgan
Previous graduates have gone on to work in financial services, insurance, investment banking and assetmanagement, across Asia, the UK and EU.
(Data provided from alumni who completed the annual destination data survey for 2020/21 and 2019/20).
Course information and statistics (2022/23 cohort)
