If you are passionate about quantitative finance, financial technology, mathematics, data analysis, and programming, and you have the determination to take on a demanding curriculum, the Master of Science in Mathematical Finance & Financial Technology (MSMFT) is meant for you.
Faculty members will guide you, world-renowned authorities in the subject areas comprising the curriculum, to develop a skill set that will set you apart in the highly competitive quantitative finance and fintech employment markets. Whether your sights are set on working in financial technology, financial data analysis, financial engineering, risk management, asset management, or quantitative analytics, you will have what it takes to succeed.
The three-semester program takes you to the cutting edge of mathematical finance and financial technology. The curriculum includes a comprehensive survey of the stochastic mathematics employed in asset pricing, risk modelling, and portfolio management. You will be exposed to the latest concepts, tools, and computational techniques employed in financial technology and data analysis, and you will have the opportunity to explore exciting new frontiers such as machine learning and algorithmic trading.
The MSMFT is a full-time, three-semester, 39-credit program that develops advanced proficiency in the following areas:
Algorithmic trading and high-frequency data
Big data analysis and cloud computing
Blockchain and cryptocurrencies
Computational expertise in R and Python
Credit risk modelling
Deep learning and financial applications
Portfolio theory and asset management
Statistical, econometric, and machine learning techniques applied to the analysis of financial data
The program comprises five areas of concentration:
Analytics & Research
You will also have the opportunity to complete an internship or industry-sponsored project in the summer, allowing you to put your newly developed skills to the test, add real-world experience to your resume, and expand your network.
The career paths that MSMFT graduates embark on include:
Algorithmic and quantitative trading
Design and valuation of financial products
Financial data analysis
Quantitative risk management