Master of Science in Computational Finance and Risk Management
The Master of Science in Computational Finance and Risk Management (MS-CompFin) is a Professional M.S. degree program offered by the Department of Applied Mathematics (AMATH) within the College of Arts and Sciences. As with other MS and Ph.D. degrees at the University of Washington, the MS-CompFin degree is awarded by the University of Washington through the Graduate School. Registration and operations for the MS-CompFin program are handled by the University of Washington Professional and Continuing Education (PCE) organization.
The MS-CompFin program is designed to address the demand in the financial services industry for advanced quantitative computational finance skills and next generation risk management skills. Individuals who understand how to manage assets to enhance investment returns while controlling risk are required throughout the world of financial services, as are individuals who understand modern risk management methods. The emerging profession of financial risk management underscores the growing importance of the latter skill set (see for example www.garp.org). For students with strong mathematical and quantitative skills, Computational Finance and Risk Management provides exciting new career paths to consider.
The main goals of the program are to:
- Deliver a highest quality M.S. degree education to current and future quantitative finance industry professionals that will enable them to be more effective in their work and able to rapidly advance in their chosen career path.
- Offer a curriculum whose course offerings educate students in best computational finance and risk management practices, including new cutting edge methods that have the potential to reduce investment risk and deliver higher risk-adjusted returns.
- The degree can be pursued in either classroom or online formats, full-time or part-time. There is no difference between the classroom and online options in the content delivered and the diploma awarded.
- Provide live online delivery and video capture of lectures and interactive class sessions using a best-of-breed approach that continually leverages advances in online delivery technology. For current delivery technology, see Online Delivery Technology.
Curriculum and Degree Requirements
The MS-CompFin curriculum offers 16 courses displayed below, for a total of 60 credits.
| Required Courses (25 credits) | Elective Courses (35 credits) | |
|---|---|---|
| AMATH
540* (5) Intro. to Computational Finance and Financial Econometrics | AMATH 548 (4)
Monte Carlo Simulation Methods in Finance | |
| AMATH 541 (4)
Investment Science | AMATH 551
(3) Foundations of Trading Systems | |
| AMATH 542 (4) Financial Data Modeling and Analysis in R | AMATH 552 (2) Portfolio Performance Analysis and Benchmarking | |
| AMATH 543
(4) Portfolio Construction and Risk Management | AMATH 553 (2) Financial Time Series Forecasting Methods | |
| AMATH 544 (4)
Options and Derivatives | AMATH 554 (2)
Endowment Investment Management | |
| AMATH 545 (4)
Introduction to Risk Management | AMATH 555 (4)
Optimization in Finance | |
Elective Courses (35 credits) | AMATH 582
(5) Computational Methods for Data Analysis | |
| AMATH 546* (5)
Quantitative Risk Management | AMATH 583
(5) High Performance Scientific Computing | |
| AMATH 547 (4)
Credit Risk Management | ||
*These two online courses are offered by the Economics Department joint listing with ECON 424 and ECON 589, respectively.
The curriculum features extensive use of the open source R programming language and modeling environment, and associated computational finance packages. See R Programming.
In order to earn the M.S. degree a student must complete the following requirements:
- At least 40 credits from the table above, including the six required courses
- A cumulative grade point average (GPA) of at least 3.2
- A final examination
Further details on the curriculum, including timing of course offerings, course descriptions, pathways, degree completion times, final exam requirements, and program pre-requisites may be found at Academics. Information on related certificate programs is provided at Certificates. For information on instructors see Faculty.
Applicant Backgrounds
This Professional MS degree program is ideally suited to individuals who have completed an undergraduate, or optionally a Master's degree, in science or engineering fields that include applied mathematics, economics, mathematics, physics, statistics, computer science or electrical engineering, and a strong academic record. The program is also suited to MBA graduates with exceptionally strong quantitative and computational skills and an exceptionally strong academic record. Further details, including admissions requirements and application information may be found at Admissions.