BSc Acoustics and Music Technology
The University of Edinburgh, a prestigious institution in the United Kingdom, offers a ...
MSc Computational Mathematical Finance
The Kings Buildings Campus
INTAKE: September
Program Overview
The MSc in Computational Mathematical Finance at the University of Edinburgh combines mathematical modeling, computational techniques, and financial theory to prepare students for challenging roles in the finance sector. This interdisciplinary program equips students with the skills to tackle real-world problems in financial markets, risk assessment, and asset pricing, using advanced mathematical and computational tools. The program is designed for students who have a strong background in mathematics, statistics, or a related field and who are looking to deepen their understanding of financial systems. Graduates of the program are well-prepared to apply quantitative methods to solve financial problems, making them highly sought-after by financial institutions, hedge funds, and investment firms.
Curriculum: The curriculum for the MSc in Computational Mathematical Finance is structured to provide students with both a theoretical foundation and practical, computational skills. Core modules include Advanced Mathematical Methods, Computational Finance, Financial Econometrics, and Stochastic Processes in Finance, which cover essential areas in financial mathematics, numerical methods, and statistical analysis. These modules enable students to develop a deep understanding of the mathematical models used in financial markets and the computational techniques needed to implement these models. Elective modules allow students to specialize further in areas such as Risk Management, Financial Engineering, and Quantitative Trading, which offer additional insights into specific sectors of the finance industry. The program also includes a dissertation component, where students conduct independent research, applying their mathematical and computational knowledge to real-world financial problems.
Research Focus: The MSc in Computational Mathematical Finance is supported by the University of Edinburgh’s renowned research community in the fields of applied mathematics, quantitative finance, and financial engineering. The university’s research centers, such as the Edinburgh School of Mathematics and the Bayes Centre, focus on innovative solutions to complex financial problems, including quantitative modeling, machine learning in finance, and financial risk management. Students have the opportunity to engage with ongoing research projects, contributing to advancements in asset pricing, portfolio optimization, stochastic modeling, and algorithmic trading. The program encourages students to undertake research in cutting-edge areas, enabling them to explore emerging trends and techniques in the evolving financial landscape.
Industry Engagement: The MSc in Computational Mathematical Finance benefits from the University of Edinburgh’s strong connections with the financial industry. Students have the opportunity to engage with industry professionals through guest lectures, seminars, and workshops, where they can gain insights into the latest developments and challenges in the finance sector. The program also offers access to internships and collaborative projects with leading financial institutions, hedge funds, and investment firms. These industry engagements provide students with valuable hands-on experience and the opportunity to apply their academic learning in real-world financial contexts. The program’s strong ties with the financial sector enhance students’ employability and ensure they are well-prepared for careers in quantitative finance, financial modeling, risk management, and more.
Global Perspective: The MSc in Computational Mathematical Finance at the University of Edinburgh emphasizes a global perspective, reflecting the interconnected nature of financial markets and the need for international solutions to financial challenges. The program attracts students from around the world, fostering a diverse and collaborative academic environment. Students are exposed to global trends and practices in financial markets and are encouraged to develop solutions to problems that transcend national borders. With the program’s focus on quantitative techniques, students are equipped to work in a globalized financial industry, addressing complex financial issues that impact economies worldwide. The global outlook of the program prepares students to work in multinational corporations, international financial institutions, or in global financial markets.
Location
The Kings Buildings Campus
Score
IELTS: 6.5
Tuition Fee
£ 38100
Postgraduate entry requirements:
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Academic Qualifications: Prospective postgraduate applicants to the University of Edinburgh are typically required to have achieved a minimum academic qualification of approximately 60%, based on their previous academic achievements and qualifications.
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English Language Proficiency:
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IELTS (International English Language Testing System): Minimum overall score of 6.5, with at least 6.0 in each component (Listening, Reading, Speaking, Writing).
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TOEFL (Test of English as a Foreign Language): Minimum score of 100 on the internet-based test (iBT), with at least 20 in each component (Reading, Listening, Speaking, Writing).
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PTE (Pearson Test of English): Minimum overall score of 70, with at least 59 in each component (Listening, Reading, Speaking, Writing).
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Students must provide:
- academic marksheets & transcripts
- letters of recommendation
- a personal statement - SOP
- passport
- other supporting documents as required by the university.
Work experience: Some postgraduate courses may require relevant work experience in the field.
It is important to note that meeting the minimum entry requirements does not guarantee admission, as the university considers factors such as availability of places and competition for the program. Additionally, some courses may have higher entry requirements or additional selection criteria, such as interviews or portfolio submissions.
The University of Edinburgh offers a range of scholarships and funding opportunities specifically designed to support international students pursuing undergraduate, postgraduate, and research programs. These scholarships aim to promote diversity, academic excellence, and global engagement.
Global Scholarships: The University of Edinburgh offers Global Scholarships to outstanding international undergraduate students. These scholarships provide financial assistance towards tuition fees and living expenses, enabling talented students from around the world to access quality education at Edinburgh.
Edinburgh Global Research Scholarships: International postgraduate students pursuing research-based programs (Ph.D., MSc by Research) can apply for Edinburgh Global Research Scholarships. These scholarships provide full or partial funding for tuition fees and living expenses during the research program.
School-specific Scholarships: Some academic schools and departments within the university offer scholarships targeting international students in specific disciplines or programs. These scholarships may be merit-based or need-based and vary in terms of eligibility criteria and funding amounts.
Commonwealth Scholarships: The University of Edinburgh participates in various Commonwealth scholarship schemes, providing opportunities for students from Commonwealth countries to study in the UK. These scholarships are funded by the UK government and other organizations.
External Funding Sources: International students are encouraged to explore external funding sources, such as government scholarships, private organizations, and international foundations, to support their studies at the University of Edinburgh.
It is important to note that scholarship availability, criteria, and application deadlines may change from year to year.
The MSc Computational Mathematical Finance program equips graduates with a unique skill set combining mathematics, finance, and programming, making them highly competitive in the global financial industry. Career opportunities span traditional finance roles to emerging fields at the intersection of finance, technology, and data science. Graduates benefit from strong industry demand, attractive salaries, and opportunities for continuous professional development and advancement.
Quantitative Analyst (Quant): Graduates of the MSc Computational Mathematical Finance program are well-suited for roles as quantitative analysts. Quants develop and implement mathematical models and algorithms to analyze financial markets, price derivatives, and optimize trading strategies. They work in investment banks, hedge funds, asset management firms, and proprietary trading desks.
Risk Analyst/Manager: Risk management is a critical function in the financial industry. Graduates with expertise in computational finance are in demand for roles as risk analysts or risk managers. They assess and manage market risk, credit risk, and operational risk using advanced quantitative techniques and statistical methods.
Financial Engineer: Financial engineering involves designing and developing sophisticated financial products and solutions. Graduates with a background in computational mathematical finance excel in roles as financial engineers, where they create innovative financial instruments, pricing models, and trading algorithms.
Algorithmic Trader: Algorithmic trading relies on quantitative models and automated strategies to execute trades in financial markets. Graduates can pursue careers as algorithmic traders, leveraging their programming skills and mathematical expertise to develop and deploy trading algorithms for optimal execution and risk management.
Data Scientist/Quantitative Developer: In an era of big data, financial institutions increasingly rely on data-driven decision-making. Graduates can work as data scientists or quantitative developers, utilizing their computational skills to analyze large datasets, build predictive models, and develop data-driven investment strategies.
Consultant in Financial Services: Consulting firms specializing in financial services value candidates with expertise in computational finance. Graduates can work as consultants, advising financial institutions on risk management, quantitative modeling, regulatory compliance, and technological innovation.
Research Analyst/Academic Career: Some graduates may choose to pursue research or academic careers, conducting advanced research in financial mathematics, computational finance, or related fields. They may work in academia, research institutes, or contribute to industry publications and journals.
Entrepreneurship and Fintech: With a solid foundation in computational finance, graduates may venture into entrepreneurship or fintech startups, leveraging their skills to innovate new financial technologies, platforms, and services.
