The MSCF course of study is a mix of traditional lectures and individual and group projects. You will learn traditional finance theories of equity and bond portfolio management, the stochastic calculus models on which derivative security trading is based and computational techniques including Monte Carlo simulation, optimization and the numerical solution of partial differential equations using C++ and Python. You will take a sequence of data science, machine learning and time series courses and apply these methods in courses on asset management, statistical arbitrage, risk management and market microstructure. A required summer internship puts the skills learned in the MSCF program to use in industry. The program concludes with a semester-long, company-sponsored project course in machine learning and a capstone course in financial engineering. A strong emphasis is placed on communication skills throughout the program.
Chartered Financial Engineer
Curriculum by the Numbers
- 22 courses in total with 48 credits
- 12 courses in finance theory
- 7 courses in quantitative techniques
- 3 courses in research
- 10 elective courses from other MSc. (Econometrics & Quantitative Risk)