Explore the Interconnection of Investing and Quantitative Analysis
Next start date
September 6, 2016
Computational finance brings together the power of computing and statistical analysis with the principles of finance and investment management. This four-course certificate program examines the mathematical, statistical and econometric principles that underlie the quantitative management of financial investments. You’ll study the mechanisms of investment science, investigate portfolio optimization and asset management, and build models of risk and return. You’ll also receive an in-depth introduction to using the R statistical programming language for financial modeling and analysis.
Experienced professionals looking to advance their career in computational finance, those who have completed the Quantitative Fundamentals of Computational Finance certificate program, or those with a degree in a related field preparing to pursue graduate study.
At a minimum, a successful candidate will meet one of the following requirements:
All applicants must show proficiency in the following subjects:
If possible, students should take the R Programming for Quantitative Finance course for an introduction to R programming.
Applicants with dated or incomplete preparatory coursework should consider taking one or more of the following courses before applying: Mathematical Methods for Quantitative Finance, Probability & Statistics for Computational Finance, Introduction to Computational Finance & Financial Econometrics.
To participate in this program, you’ll need to have advanced English language skills. To learn more, see English Language Proficiency Requirements.
International students are welcome to apply to an online offering of this program, which doesn’t require a visa. To enroll in a classroom offering, you must have a visa that permits study in the United States. This certificate program does not enable students to obtain or maintain F-1 visa status. For more information, see Admission Requirements for International Students.
A computer with a high-speed Internet connection is required. Students with data transfer caps on their connection should be prepared to allocate at least 3 GB per week for lecture videos. Students may be required to install Web conferencing software for some course activities.
You earn the certificate by regularly attending class and successfully completing all required courses. For more information, see Completing Your Program.
This program offers partial preparation for the Financial Risk Manager certification by the Global Association of Risk Professionals and the Chartered Financial Analyst certification by the CFA Institute.
By completing this certificate program, you can earn up to 12 graduate credits toward degree requirements should you later be accepted into the Master of Science in Computational Finance & Risk Management (classroom or online program). To use these credits, you must obtain graduate nonmatriculated status before you register for the first course of the certificate program.
Visit the Computational Finance & Risk Management program website for more details and to sign up for email updates.
Complete the courses listed below to earn the certificate. You may be able to take individual courses without enrolling in the certificate program; check the course pages for details.
Investment Science I (CFRM 540)
Investment Science II (CFRM 541)
Financial Data Modeling & Analysis in R (CFRM 542)
Portfolio Optimization & Asset Management (CFRM 543)
Certificate in Computational Finance
Approved by the UW Department of Applied Mathematics in collaboration with the UW Department of Economics.
We’re currently accepting applications and will be reviewing them in the order they’re received. We’ll accept applications until the program closes.
We’ll contact you within two to five weeks of receiving your application materials to let you know if you’ve been accepted to the program.
If you’re accepted, we’ll send you details about your first-term course, including information on paying your course fee. Your course fee is due two weeks before the first class.
With the exception of the one-time application fee, certificate program fees are charged on a quarterly basis. Payment is due when you register.
Course fees do not include any costs for class materials such as textbooks and software. The technology fee is based on the number of credits you are taking. It is not charged during summer quarter.
Drops, Withdrawals & Refunds
Courses are offered 100 percent online. The flexible online format allows you to access course content wherever you are, on your own schedule. You simply need to complete assignments by their due dates. Video lectures, assignments and other course materials are delivered through a Web-based learning management system, such as Canvas or Moodle, which also serves as a hub for communicating with your instructors and classmates. You can stream video lectures as they are delivered live or view recordings at a later time.
Our special blended programs combine the convenience of online study with the vibrancy of in-person classes for a unique learning experience.
Not available for this program
Attend class in person at one of our convenient locations. You’ll engage face to face with your classmates and instructors as part of a highly interactive curriculum. An online learning management system may be required to access some course materials and assignments.
CompFin Program Director
Principal Consultant, www.R-Programming.org
Discover how to apply cutting-edge tools and techniques to extract meaning from data sets ranging in size from gigabytes to petabytes.
Increase your knowledge in applied mathematics and complement your area of expertise, whether your career is in engineering, manufacturing, education or research.
Learn how to enhance investment returns by studying portfolio construction as well as asset and financial risk management methods.
Develop the foundational skills needed for the quantitative management of investments. Learn the mathematical and statistical concepts used in managing portfolios and planning risk strategies.
Study the fundamentals of R programming. Learn the structure and organization of the R environment and practice accessing and running R packages.