Core Values
Awards
Student Activities
Publications
The Computational Finance & Risk Management program is a self-sustaining interdisciplinary offering at the University of Washington. Established by the Department of Applied Mathematics at the University of Washington, the CFRM program offers rigorous and relevant instruction grounded in both theory and practice. Recognizing the rapidly changing landscape in finance, CFRM adapts to equip students with skills and knowledge that will enable them for future success.
CORE VALUES
Diversity: Courses cover a broad array of topics that allow students to become well versed in the worlds of finance, risk management, and computing.
Rigor: Instructors and peers expect students to commit to the intellectual investment by devoting themselves to learning the theory and practice of quantitative finance and financial risk management, assuring a depth of understanding and competitive candidates upon graduation.
Interdisciplinary approach: Combined support from multiple departments enables students to gain advanced knowledge in applied mathematics, economics, statistics, finance, and computing.
Adaptability: Students are encouraged to provide feedback to instructors and courses. Constructive criticism has resulted in curriculum that is better adapted to the requirements of both the market and the student.
Global Citizenship: CFRM’s educational environment strengthens the emerging demographics in the financial services community by placing an emphasis on gender balance, cultural diversity, and an international focus that helps to produce global citizens aware of their impact and that of their profession on the world.
Practicality: Providing ties to the finance industry including instruction from finance industry professionals, seminars on trends and relevant topics, and special on-site events keeps the student experience rooted in the real world.
Accessibility: Using online learning technologies to support students participating remotely, as well as for the supplemental use of classroom students, helps to extend access to students in the broadest way possible.
AWARDS
The University of Washington is a world-class institution, and is recognized globally as a leader in education.
Why you should choose UW for graduate school:
- CFRM was ranked #16 in QuantNet’s 2026 Ranking of “Best Financial Engineering Programs“
- Department of Applied Mathematics Awards
- CNBC ranks UW 1st among “public US schools that pay off the most.”
- US News ranks UW 8th among world universities in the “2025 Best Global Universities Rankings.“
- University Research Stats & Rankings
- UW News: Honors and Awards
STUDENT ACTIVITIES
UW Actuarial Club
The UW Actuarial Club is ideal for students who have an interest in actuarial science. The club is dedicated to learning about the actuarial profession, networking with students and local actuaries, and gaining new skills. For more information, please visit their website.
UW Algorithmic Trading Club
The UW Algorithmic Trading Club is for students who like to apply programming, statistics, and mathematics to solve algorithmic trading and other financial problems. It is open to students and faculty of all backgrounds and levels of experience. Find out more on their LinkedIn or Facebook pages.
UW Foundation for International Understanding Through Students (FIUTS)
Based on the Seattle campus, FIUTS programs create a community of international and American students, members of the local community, and alumni around the world. Open to all, FIUTS delivers programs to a diverse range of constituents that promote cross-cultural understanding, global culture, and respect for diversity. Such programming includes Conversation Groups, excursions around Seattle and Puget Sound, and more. For more information, please visit their website.
Formal and Informal Study Groups
CFRM students are encouraged to develop ad-hoc study groups on campus to collaborate on teaching and learning, as well as preparation for exams in the program and professional certifications. Students studying for CFA, FRM, SOA, or other professional certification exams may especially benefit from collaboration, and space is available in Lewis Hall for this purpose.
PUBLICATIONS
Many CFRM students are actively engaged in academic research on problems in computational finance and risk management.
There is an ever-growing list of publications written by our current CFRM students and alumni.
| CFRM Authors | Title | Link | Publication Year |
| Lin, Jimin UW CFRM '18 | Jimin Lin & Matthew Lorig (2019) On Carr and Lee’s Correlation Immunization Strategy, Applied Mathematical Finance, 26:2, 131-152, DOI: 10.1080/1350486X.2019.1598276 | Paper | 2019 |
| Nguyen, Hung UW CFRM '19 | Leung, T. and Nguyen, H. (2019), "Constructing cointegrated cryptocurrency portfolios for statistical arbitrage", Studies in Economics and Finance, Vol. 36 No. 3, pp. 581-599. | Paper | 2019 |
| Brownson, Gregory; Cao, Loc; Lewis, Tommy; Mauer, Dominic; Nguyen, Hung; Sneeringer, Jack | Paper: Research Challenge on the Relationship Between Momentum Trading and Options Strategies | Paper | 2018 |
| Lin, Jimin UW CFRM '18 | Paper: The Quadrant Probabilities of Paired Financial Time Series | SSRN | 2018 |
| Nguyen, Hung UW CFRM '19 | Paper: Constructing Cointegrated Cryptocurrency Portfolios for Statistical Arbitrage | SSRN | 2018 |
| Uthaisaad, Chindhanai UW CFRM '18 | Thesis: Skew-t Information Matrix: Evaluation and Use | Thesis | 2018 |
| Uthaisaad, Chindhanai UW CFRM '18 | Uthaisaad, C. (2018). the R package skewtInfo | skewtInfo | 2018 |
| Uthaisaad, Chindhanai UW CFRM '18 | Uthaisaad, C. and Martin, R. D. (2018). “The Azzalini Skew-t Information Matrix Evaluation and Use for Standard Error Calculations”. | SSRN | 2018 |
| Brownson, Gregory UW CFRM '19 | Brownson, G. (2018). “Shiny User Interface (UI) to the RobStatTM R Package”, with Vignette | RobStatTM-GUI | 2018 |
| Acharya, Avinash UW CFRM '17 | Acharya, A. (2017). Development of fundamental factor model part of R package factorAnalytics | factorAnalytics | 2017 |
| Acharya, Avinash UW CFRM '17 | Martin, R. D., Acharya, A., and Yi, Lingjie (2017). “Fundamental Factor Model Vignette” | Vignette | 2017 |
| Simonson, Jack UW CFRM '17 | Paper: High-Frequency ETF Pairs Trading | SSRN | 2017 |
| Arora, Rohit UW CFRM '16 | Martin, R. D. and Arora, R. (2017). “Inefficiency of Modified VaR and Expected Shortfall”, Journal of Risk, 19(6), 59-84. | Paper | 2017 |
| Arora, Rohit UW CFRM '16 | Thesis: Variability in Modified Estimators of VaR and ES | Thesis | 2016 |
| Chawla, Shaily UW CFRM '17 | Paper: Investigating the Price Dynamics between Europe ETFs: EZU vs FEZ | SSRN | 2016 |
| Arora, Rohit UW CFRM '16 | Arora, R. (2015). R package covmat. | Covmat | 2015 |
Faculty advisors include Associate Professor Tim Leung, Associate Professor Matthew Lorig, and Professor Emeritus Doug Martin.