Financial Mathematics MSc

Program Overview

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The MSc in Financial Mathematics at Bayes Business School provides a rigorous and quantitative approach to finance, focusing on mathematical modelling and analysis. Students develop strong analytical and problem-solving skills, a deep understanding of financial markets and instruments, and the ability to apply their knowledge to real-world problems. Graduates are highly sought-after by leading financial institutions and corporations worldwide for careers in quantitative analysis, financial engineering, risk management, and other finance-related roles.

Program Outline

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Degree Overview:

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Objectives:

• The program focuses on mathematical concepts used by quants, including stochastic modelling, simulation techniques, and econometrics.
• Students will learn about asset pricing, risk management, and different financial securities, including equities, fixed income, and derivatives.
• Graduates will be equipped for a variety of careers in finance and related areas, in the UK and around the world.

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Description:

• The program offers a rigorous and quantitative approach to finance, with a focus on mathematical modelling and analysis.
• Students will develop strong analytical and problem-solving skills, as well as a deep understanding of financial markets and instruments.
• The program also provides students with the opportunity to apply their knowledge and skills to real-world problems, through projects and simulations.

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Outline:

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Program Content:

• Derivatives: This module introduces derivative instruments and markets in the context of risk management.
• Stochastic Modelling Methods in Finance: This module provides the necessary mathematical tools for quantitative finance, including Brownian motions and stochastic calculus.
• Asset Pricing: This module focuses on pricing financial securities and explores fundamental theories, portfolio theory, CAPM, and factor models.
• Fixed Income: This module provides a thorough introduction to fixed income securities and the latest modelling streams.
• Risk Analysis: This module examines quantitative approaches to financial risk, focusing on evaluation, management, and research.
• Advanced Stochastic Modelling: This module delves into financial mathematics beyond the standard Black-Scholes model, covering exotic contracts and non-Gaussian models.
• Simulations Techniques and Financial Modelling: This module focuses on applying numerical methods and programming languages to finance, covering scenario generation, optimization, and Python/Matlab applications.
• Elective Modules: Students can choose from various electives in their final term, including Business Research Project, Applied Research Project, or specialized modules like Applied Machine Learning, Trading and Hedging in the Forex Market, and more.

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Program Structure:

• The program is full-time and takes 12 months to complete.
• Students take a combination of core modules and electives throughout the year.
• In the final term, students can tailor their degree by choosing elective modules or undertaking a research project.

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Course Schedule:

• Term 1: September to December
• Term 2: January to April
• Term 3: May to July

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Individual Modules:

• Each module has its own learning objectives, teaching methods, and assessment criteria.
• For detailed information about individual modules, please refer to the downloadable course specification document linked on the page.

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Assessment:

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Assessment Methods:

• Coursework
• Examinations
• Presentations
• Groupwork
• Problem sets

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Assessment Criteria:

• Students are assessed on their knowledge, understanding, and application of the concepts covered in each module.
• Specific assessment criteria and weighting may vary depending on the individual module.

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Teaching:

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Teaching Methods:

• Interactive lectures
• Seminars
• Workshops
• Case studies
• Practical exercises

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Faculty:

• The program is taught by experienced faculty members with expertise in the relevant areas.
• Faculty members have extensive industry experience and research backgrounds.

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Unique Approaches:

• The program emphasizes a hands-on learning approach, with a focus on applying theory to real-world scenarios.
• Students have access to industry-standard software and tools, including Bloomberg terminals and Python/Matlab platforms.

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Careers:

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Career Paths:

• Quantitative Analyst
• Financial Engineer
• Data Scientist
• Risk Analyst
• Trader
• Portfolio Manager

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Opportunities:

• The program equips students with the skills and knowledge needed for a successful career in finance.
• Graduates are highly sought-after by leading financial institutions and corporations worldwide.

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Outcomes:

• Recent graduates have secured positions at renowned companies such as Google, Goldman Sachs, Barclays, and JP Morgan.

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Other:

• The program includes induction weeks with refresher courses and introductions to careers services and networks.
• Students can choose to attend international electives in locations like Italy and the USA.
• The program has strong links to major players in the finance industry, providing students with networking and internship opportunities.

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Tuition fees are subject to annual change. 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).