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Computational Finance MS degree

Ashok Robin, Program Director

Program overview

The master of science in computational finance is designed for students interested in computational or quantitative finance careers in banking, finance, and a growing number of additional industries. Professionals in these fields use their strengths in business, modeling, and data analysis to understand and use complex financial models, often involving differential and stochastic calculus.

The program addresses a vital and growing career field, reaching beyond banking and finance. Typical job titles include risk analyst, research associate, quantitative analyst, quantitative structured credit analyst, credit risk analyst, quantitative investment analyst, quantitative strategist, data analyst, senior data analyst, fixed income quantitative analyst, and financial engineer.

Computational finance is an excellent career option for technically-oriented professionals in the fields of business, math, engineering, economics, statistics, and computer science. Programming knowledge is highly preferred.

Plan of study

The curriculum offers an integration of finance, mathematics, and computing. The required mathematics courses have substantial financial content and the experiential computational finance course, which students take during the summer, makes use of skills learned in the mathematics, analytics, and finance courses taken up to that point. The program has a strong multidisciplinary nature and combines the expertise of four of RIT's colleges. The program is a full-time, 12- to 17-month curriculum beginning in the fall or spring. The program ends with a required non-credit comprehensive exam based on the courses completed by the student.


Computational finance, MS degree, typical course sequence

Course Sem. Cr. Hrs.
ACCT-603 Accounting for Decision Makers 3
FINC-671 Survey of Finance 3
FINC-772 Equity Analysis 3
FINC-773 Debt Analysis 3
FINC-774 Advanced Derivatives 3
MATH-735 Mathematics of Finance I 3
MATH-736 Mathematics of Finance II 3
  Analytics Electives 6
  Electives 6
FINC-791 Computational Finance Exam Preparatory 0
FINC-795 Computational Finance Experience 3
Total Semester Credit Hours 36

Analytics electives*

FINC-780 Financial Analytics
MKTG-768 Marketing Analytics
STAT-611 Statistical Software
STAT-747 Principles of Statistical Data Mining

* Additional electives are available with approval.

Admission requirements

To be considered for admission to the MS program in computational finance, candidates must fulfill the following requirements:

  • Complete a graduate application
  • Hold a baccalaureate degree (or equivalent) from an accredited university or college.
  • Submit official transcripts (in English) of all previously completed undergraduate and graduate course work.
  • Submit a personal statement of educational objectives. Statement should indicate any mathematical and programming knowledge held by the candidate as well as their professional interests, and why these make the candidate suitable for the program.
  • Submit a current resume or curriculum vitae.
  • International applicants whose native language is not English must submit scores from the TOEFL, IELTS, or PTE. A minimum TOEFL score of 92 (internet-based) is required. A minimum IELTS score of 7.0 is required. The English language test score requirement is waived for native speakers of English or for those submitting transcripts from degrees earned at American institutions.

For further information about tips on personal statements and additional guidance on how to submit a successful application, please visit Saunders College of Business Admissions Requirements.