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The Kings Buildings Campus
INTAKE: September
The MSc Computational Mathematical Finance program at The University of Edinburgh is designed to provide students with a comprehensive understanding of financial mathematics, computational techniques, and quantitative analysis in the context of the financial industry. Through a combination of rigorous theoretical training and practical applications, students develop the skills necessary to tackle complex financial problems and make informed decisions in dynamic markets.The MSc Computational Mathematical Finance program equips graduates with a unique blend of mathematical expertise, computational skills, and financial knowledge highly sought after in the finance industry. Graduates pursue diverse career paths as quantitative analysts, risk managers, financial engineers, and algorithmic traders in investment banks, hedge funds, consulting firms, and other financial institutions.
Advanced Mathematical Techniques: The program offers a deep dive into mathematical concepts essential for financial modeling, including stochastic calculus, partial differential equations, and numerical methods. Students gain proficiency in applying mathematical techniques to analyze financial derivatives, risk management strategies, and pricing models.
Computational Finance Tools: With a strong emphasis on computational methods, students learn to implement mathematical models using programming languages such as Python, MATLAB, and R. Through hands-on projects and simulations, they develop practical skills in coding, data analysis, and algorithmic trading.
Financial Markets and Instruments: The curriculum covers a wide range of topics related to financial markets, instruments, and institutions. Students explore the dynamics of equity, fixed income, and derivative markets, as well as the role of financial institutions, regulatory frameworks, and macroeconomic factors.
Risk Management and Portfolio Optimization: Understanding and managing risk is crucial in financial decision-making. Students learn various risk measurement techniques, including value-at-risk (VaR), stress testing, and scenario analysis. They also explore portfolio theory and optimization methods to construct efficient investment portfolios.
Industry-Relevant Projects and Internships: The program offers opportunities for students to engage in industry collaborations, internships, and research projects with leading financial institutions, hedge funds, and asset management firms. These practical experiences allow students to apply their knowledge in real-world settings and build valuable connections in the finance industry.
Career Development Support: The University of Edinburgh provides extensive career development support, including networking events, workshops, and access to alumni networks. Career services assist students in securing internships, job placements, and preparing for interviews in finance-related roles.
The Kings Buildings Campus
IELTS: 6.5
£ 38100
Postgraduate entry requirements:
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.
English Language Proficiency:
IELTS (International English Language Testing System): Minimum overall score of 6.5, with at least 6.0 in each component (Listening, Reading, Speaking, Writing).
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).
PTE (Pearson Test of English): Minimum overall score of 70, with at least 59 in each component (Listening, Reading, Speaking, Writing).
Students must provide:
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.