MSc Accounting and financial Management
The MSc Accounting and Financial Management course at Royal Holloway University of Lond...
MSc Computational Finance (with a Year in Industry)
Egham Campus
INTAKE: September
Program Overview
The MSc Computational Finance (with a Year in Industry) program at Royal Holloway University of London is a specialized course designed to provide students with a deep understanding of both finance and computational methods. It combines rigorous academic training with practical industry experience, offering students the opportunity to gain real-world exposure and enhance their employability in the field of computational finance.
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Financial Theory and Practice: The program covers core concepts and theories in finance, including asset pricing, portfolio management, risk management, and derivatives. Students develop a solid understanding of financial markets, instruments, and investment strategies.
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Computational Methods in Finance: Students learn to apply computational techniques and programming languages to solve complex financial problems. They acquire skills in programming languages such as Python and R, and gain hands-on experience in developing and implementing financial models and algorithms.
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Financial Econometrics: The course focuses on the application of statistical and econometric methods to financial data analysis. Students learn how to model and forecast financial variables, analyze financial time series, and estimate econometric models using software tools.
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Algorithmic Trading and High-Frequency Finance: Students explore algorithmic trading strategies and the role of technology in financial markets. They learn about market microstructure, order book dynamics, and the design and implementation of automated trading systems. The course also covers high-frequency finance and the associated challenges and opportunities.
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Risk Management and Quantitative Risk Analysis: Students gain insights into risk management techniques and tools used in the financial industry. They learn how to measure and manage financial risks, including market risk, credit risk, and operational risk. The course also covers quantitative risk analysis methods, such as value-at-risk and stress testing.
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Financial Data Analytics and Big Data: Students learn how to analyze and interpret large financial datasets using data analytics techniques. They gain proficiency in data manipulation, visualization, and machine learning algorithms applied to financial data. The course also addresses ethical considerations in handling financial data.
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Industry Placement (Year in Industry): This program offers students the unique opportunity to undertake a year-long industry placement within the finance sector. Students gain practical experience, apply their academic knowledge to real-world problems, and develop valuable industry connections. The industry placement enhances their employability and provides insights into the dynamics of the financial industry.
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Dissertation: Students undertake an independent research project, applying computational finance techniques to a specific topic of interest. They work closely with academic supervisors and industry professionals to conduct in-depth research and present their findings in a dissertation.
Location
Egham Campus
Score
IELTS:6.5
Tuition Fee
£ 22000
Postgraduate Entry Requirements:
- Applicants should have successfully completed a bachelor's degree or its equivalent from a recognized institution with a minimum overall score of 60% to 65% or equivalent.
- English language proficiency is required, and applicants must provide evidence of their English language skills through an approved language test.
- IELTS: A minimum overall score of 6.5 with no individual component below 6.0.
- PTE Academic: A minimum overall score of 61 with no individual score below 54.
- Some postgraduate programs may have specific subject prerequisites or additional requirements.
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.
Royal Holloway, University of London offers a range of scholarships to support students in their academic pursuits. These scholarships are designed to recognize excellence and provide financial assistance to eligible students.
- Founder's Scholarship: This is the most prestigious scholarship at Royal Holloway, awarded to undergraduate students who demonstrate exceptional academic achievement and potential. It covers full tuition fees and provides a generous annual stipend.
- Royal Holloway Excellence Scholarship: This scholarship is awarded to undergraduate students based on their academic achievement and potential. It offers a £2,500 tuition fee waiver for each year of study.
- International Excellence Scholarship: This scholarship is specifically for international undergraduate students. It provides a tuition fee reduction of £4,000 per year for the duration of the program.
- Masters Scholarships: Royal Holloway offers a variety of scholarships for postgraduate students, including the RHUL Principal's Masters Scholarship, the RHUL International Excellence Masters Scholarship, and subject-specific scholarships.
- Sports Scholarships: These scholarships are available to students who excel in sports and have the potential to represent the university at a high level. They provide support in the form of financial assistance and access to training facilities.
It's important to note that scholarship availability, eligibility criteria, and application deadlines may vary.
The MSc Computational Finance (with a Year in Industry) program at Royal Holloway University of London opens up diverse career prospects for graduates in the field of computational finance.
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Quantitative Analyst: Graduates can work as quantitative analysts, applying their computational and analytical skills to develop mathematical models and algorithms for pricing financial instruments, risk management, and trading strategies.
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Risk Manager: Graduates can pursue careers in risk management, assessing and mitigating financial risks for banks, investment firms, or insurance companies. They use computational tools and quantitative techniques to measure and manage various types of risk.
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Data Scientist in Finance: Graduates can work as data scientists, analyzing large financial datasets and extracting meaningful insights using advanced data analytics techniques. They contribute to the development of data-driven decision-making strategies in finance.
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Financial Technology Specialist: Graduates can work in the field of financial technology (FinTech), focusing on the development and implementation of innovative solutions in areas such as algorithmic trading, blockchain technology, or data analytics in finance.
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Portfolio Manager: Graduates can pursue careers as portfolio managers, responsible for managing investment portfolios and making strategic investment decisions. They use computational finance tools and quantitative models to optimize portfolio performance and manage risk.
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Researcher or Academic: Graduates can pursue further research or academic careers, conducting cutting-edge research in computational finance or teaching finance and computational methods at universities and research institutions.
The MSc Computational Finance (with a Year in Industry) program at Royal Holloway University of London provides students with a comprehensive skill set in finance and computational methods, preparing them for exciting and challenging careers in the finance industry. The combination of academic training, industry placement, and practical experience equips graduates with the knowledge, expertise, and practical skills necessary to excel in the field of computational finance.
