Technology and Algorithmic Finance Track
Graduates of the Technology and Algorithmic Finance Track are actively involved in the development and implementation of the entire spectrum of algorithmic trading strategies, software applications, databases and networks used in modern financial services firms. The techniques it applies bridge computer science and finance to prepare graduate to participate in large-scale and mission-critical projects. Applications include high frequency finance, behavioral finance, agent-based modeling and algorithmic trading and portfolio management.
Upon graduation, students of the Technology and Algorithmic Finance track will have developed software projects ranging from behavioral models to bespoke derivative valuations to financial trading, information management and tools and financial platforms. Students would be familiar with the use and role of technology in front, middle, and back offices; common trading strategies and how to implement and back-test them; and how to create new models and build new useful tools quickly.
Required to Complete the Financial Engineering MS program:
- 5 core courses, each 3 credits totaling 15 credits
- Track-required courses totaling 7.5 credits
- 1 required applied lab worth 1.5 credits
- 6 credits of electives
- 1 capstone experience of 3 credits
- Capstone assessment (0 credits)
- Bloomberg certification (0 credits)
Total # of credits: 33
3 Courses from the Following:
Recommended Electives (6 credits):
Recommended Labs (1.5 credits*):
The following are recommended labs for this track:
*FRE-GY 6883 counts both as a lab (1.5 credits) and as an elective (1.5 credits), totaling 3 credits.