Master of Science in Quantitative Finance (MQF)
Singapore, Singapore
DURATION
12 up to 24 Months
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
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EARLIEST START DATE
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STUDY FORMAT
On-Campus
Key Summary
Scholarships
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Introduction
The Master of Science in Quantitative Finance (MQF) by coursework is a full-time programme to be completed within 12 months. It caters to a need identified by the Monetary Authority of Singapore (MAS) - to groom a critical mass of specialists in quantitative finance, which is the objective underlying the second phase of MAS's Finance Scholarship Programme.
Participants can pursue their master studies in two ways: (1) The Singapore-Based Track, or (2) The International Track.
Singapore-Based Track
Participants will take all their courses at SMU (Singapore) and obtain an SMU MQF Degree.
This is the preferred path for those who are already working in Singapore or who are unable to spend four months in London at the international track. On top of being Association to Advance Collegiate Schools of Business (AACSB) and European for Management Development Quality Improvement System (EQUIS) accredited, the Lee Kong Chian School of Business is also highly ranked for its research productivity, teaching effectiveness, graduate employability and international reputation.
International Track
Participants will take their Term 1 and Term 4 courses at SMU (Singapore), and Term 2 and Term 3 courses at Bayes Business School (London, UK), and graduate with a Joint MQF degree from both institutions.
Program Outcome
The mission of the MQF programme is to produce high-quality professionals who will be highly sought after by global and regional banks, quantitative hedge funds, asset management companies, as well as regulators in Singapore.
As the global financial industry is getting more sophisticated in risk management, product innovation, and proprietary trading, the demand for quantitative finance professionals is on the rise.
Our MQF programme is positioned to flourish with this rising trend.
Curriculum
To satisfy the requirements of this master’s degree programme, students must successfully complete nine core courses and four electives. The programme duration for both the SMU's MQF local track and the international track is both 12-months, while the part-time track is a 24-month programme. Students may choose to specialise in one of the following elective tracks: Financial Data Science, Algorithmic Trading, and Risk Analytics.
The SMU MSc in Quantitative Finance is designed to equip students with both an in-depth knowledge of quantitative finance and a business-oriented, entrepreneurial mindset. As such, the curriculum will bridge both theory and practice, helping students to build up expertise and skillsets which can be immediately applied to solving real-world problems.
The curriculum consists of 9 core modules and 4 elective modules. Students have the option to specialise in either one of the elective tracks.
Term 1: 4 Core Modules
- Asset Pricing
- Stochastic Modelling in Finance
- Quantitative Analysis of Financial Markets
- Programming and Computation Financial
Term 2: 5 Core Modules
- Derivatives
- Fixed Income Securities
- Risk Analysis
- Numerical Methods
- Econometrics of Financial Markets
Term 3: 4 Elective Modules
- Financial Data Science
- Quantitative Trading Strategies
- C++ for Financial Engineering
- Financial Data Science
- Machine Learning & Financial Application
- Algorithmic Trading
- Quantitative Trading Strategies
- Portfolio Management
- C++ for Financial Engineering
- Hedge Funds
- Risk Analytics
- Credit Risk Models
- Portfolio Management
- Financial Data Science
- Machine Learning & Financial Application
Admissions
Career Opportunities
SMU has a comprehensive job placement scheme to connect our MQF students to many employment opportunities. The results of our annual survey show that SMU MQF graduates mostly find jobs in investment banks, commercial banks, asset management companies, financial IT firms, consultancies, investment research/advisory firms, insurance companies, exchanges, regulators, brokerages, financial data providers, and oil companies.