Computational Finance Certificate

Learn the key mathematical, statistical and econometric foundations needed for quantitative management of financial investments. Study classical methods of portfolio construction based on volatility as a risk measure. Learn modern theory of portfolio optimization, examine how to minimize risk, discover how to balance alpha generation versus downside risk and study the latest risk budgeting techniques. Complement your foundational knowledge with training in open source R programming language for quantitative finance modeling and analysis.

What the Certificate covers:

  • Mathematics of fixed income, interest rates and terms structure
  • Introduction to forwards, futures and options pricing and hedging use
  • Linear regression factor models and their uses in finance
  • Introduction to statistical analysis of financial data with R
  • Advanced R modeling tools for financial time series and portfolios
  • Classic mean-variance risk portfolio optimization and risk management 
  • Post-modern tail-risk based portfolio optimization and risk management



A Computational Finance Certificate will be awarded to individuals who successfully complete the following four online courses from graduate-level CFRM curriculum for a total of 14 credits:

  • September: CFRM 540, Investment Science I  (2 credits) 
  • Autumn: CFRM 541, Investment Science II   (4 credits) 
  • Winter: CFRM 542, Financial Data Modeling and Analysis in R    (4 credits) 
  • Spring: CFRM 543, Portfolio Optimization and Asset Management     (4 credits)

It is recommended that all students accepted to the Computational Finance Certificate take CFRM 463: R Programming for Quantitative Finance as an introduction to R programming.



All applicants must show competency in the following course content areas:

  • CFRM 460: Mathematical Methods for Quantitative Finance, or equivalent
    • Upcoming UW for-credit sessions can be found here. Free course materials are available on
  • CFRM 461: Probability & Statistics for Computational Finance, or equivalent
    • Upcoming UW for-credit sessions can be found here. Free course materials will be available soon on
  • CFRM 463: R Programming for Quantitative Finance, or equivalent
    • Upcoming UW for-credit sessions can be found here. Registered Computational Finance Certificate students can obtain materials for self-study. Self study is not recommended for students without prior R programming experience, as all Computational Finance Certificate courses make extensive use of the R language.


Students accepted to the CF Certificate will be taking classes with MS-CFRM students on-campus and online. In addition to proficiency requirements, applicants are expected to hold a bachelor's degree.



To Apply for the online Computational Finance Certificate click here.


Other Certificate Information

Pursue a MS-CFRM degree with graduate credit from the Computational Finance certificate. Upon successful completion of the certificate program courses and acceptance into the MS-CFRM program, students will be able to transfer up to 12 certificate credits toward the MS degree.

If you are considering this option, you must apply for UW Graduate Non-Matriculated (GNM) status at the same time you apply to the certificate program. Details are provided in the Graduate Non-Matriculated Application.

Finance industry professionals and other students taking a course in one of the Certificate programs, possibly on a single course enrollment (SCE) basis, may wish to take the course on a pass or fail basis. Such students may elect to have a course graded S/NS by paying a $20 fee at the time of registering for the course or until approximately the 8th week of the course. For option details please see Nontraditional Grading Options.

NOTE: This option is not recommended for students with GNM status who intend to pursue the MS-CFRM degree. Numeric grades are required for courses whose credit is to be applied toward the MS degree.