Ph.D. Program

PhD Program with Certificate in Quantitative Finance

The interdisciplinary Ph.D. program with concentration in Quantitative Finance trains students for academic and research positions in quantitative finance and risk management areas. It gives graduates an edge in the job market by having substantial expertise in key disciplines related to Quantitative Finance: finance, operations research, statistics, mathematics, and software development. It is focused in teaching and research on design, development, and implementation of new financial and risk management products, processes, strategies, and systems to meet demands of various institutions, corporations, governments, and households. The emphasis is on an interdisciplinary approach requiring knowledge in finance, economics, mathematics, probability/statistics, operations research, engineering, and computer science.

Students take basic courses in the involved department of the University of Florida and satisfy the requirements of the Ph.D. program in the department. Also, students take courses (from the approved list) in other departments involved in the program to satisfy requirements of the concentration. Dissertation research is conducted in quantitative finance, risk management, and relevant areas involving quantitative finance approaches. The students receive, in addition to Ph.D. degree, a Certificate in Quantitative Finance.


The interdisciplinary concentration involves four departments at the University of Florida:Industrial and Systems Engineering (College of Engineering),Mathematics (College of Liberal Arts & Sciences),Statistics (College of Liberal Arts & Sciences),Finance, Insurance, and Real Estate (College of Business).To be eligible for the Ph.D. interdisciplinary concentration, a student must be admitted to the Ph.D. program in one of the participating (hosting) departments. Students seeking admission to the concentration should have strong quantitative skills and a degree in one of the relevant fields such as finance, engineering, statistics, or mathematics. Students with a background in several disciplines are welcome. Applications should be submitted to the departments involved in the program.


The hosting department that recruited the Ph.D. student will take responsibility for financial support of the student and supervision of the student. Dissertation research should be conducted in the area of risk management, quantitative Finance and relevant areas involving quantitative finance approaches. For each student involved in the program, the hosting department forms a supervisory committee. Generally, the Chair of the supervisory committee comes from this department and the committee involves at least one faculty from other departments participating in the program.


The minimum credit hours for a Ph.D. with concentration in Quantitative Finance is 90 hours. For master’s degree hours to be counted, they must satisfy the usual requirements (see graduate catalog). A Ph.D. student should take basic courses in his/her department and satisfy the requirements of the Ph.D. program in his/her department. Also, the student should take at least six courses (from the approved list) in other departments involved in the program (excluding his/her department). This requirement can be waived if a student can demonstrate that he/she has taken the appropriate Ph.D. level courses before joining the program.


The program is administered by a committee consisting of one member from each department nominated by the chair of the department. The committee appoints a chair of the program. The appointment is for a three-year term. The current committee involves the following representatives from the departments:

  • Stanislav Uryasev (ISE)
  • Murali Rao (Math.)
  • M. Nimalendran (FIRE)
  • George Casella (Stat.)


(in addition to required courses in the departments)

FIRE Department

  • FIN 7446, Financial Theory (Fall)
  • FIN 7808, Corporate Finance (Fall)
  • FIN 7848, Market Microstructure (Spring)

Mathematics Department

  • MAP 6467, Stochastic Differential Equations (Fall)
  • MAP 6468, Stochastic Differential Equations II (Spring)
  • MAT 6932, Mathematics of Financial Derivatives (Fall)

Statistics Department

  • STA 6934 Simulation (Statistical Computing) (Fall)
  • STA 6857 Applied Time Series Analysis (Spring)
  • STA 6208, Regression Analysis (Spring)

ISE Department

  • EIN 6357, Advanced Engineering Economy (Spring)
  • ESI 6912, Introduction to Stochastic Optimization (Fall)