Print Friendly printer friendly
 Mathematical Finance

**Sorry, we are not accepting applications to the Math Finance program at this time. If you are still interested in financial mathematics next year please get back in contact then**

The Department of Mathematics in conjunction with the Institute of Applied Mathematics (IAM) offers an interdisciplinary M.Sc. program in Mathematical Finance. This 20 month program trains qualified students for either a career in the finance industry, or further study leading to the Ph.D. degree. Students can build their expertise in quantitative finance through a combination of core courses in mathematical finance combined with mathematical, comptutational, statistical courses as listed below.

The program provides a number of special features that give its students an edge:

  • Internship component providing practical industrial training in quantitative finance
  • Multi-disciplinary curriculum that combines quantitative training together with financial background. The program provides access to complementary mathematical, computational, and statistical training, providing great flexibility for understanding today's markets.
  • Development of professional skills through workshops
  • Close contact with industry members of the program's Advisory Board and beyond

    In cooperation with MITACS, Mathematics for Information Technology and Complex Systems, the program includes an industrial internship component. Each student in the program is expected to do a four month internship as part of their training. As part of the preparationi for the internship, each student is required to participate in at least two professional development/soft skills workshops offered by MITACS and to collaboratively submit the proposal for the research internship together with the company representative(s).

    The program is offered jointly by the Departments of Mathematics and Statistics (Faculty of Science) and the Finance Division (Faculty of Commerce and Business Administration). Students may apply to enter the program either through the Division of Finance or through the Mathematics or Statistics Departments. In addition to the requirements listed below, students must satisfy the general requirements of the Faculty of Graduate Studies and any applicable Departmental or Divisional requirements.

    Applicants must have a strong academic background showing good analytical skills and a Bachelor degree. In particular, students entering through the Mathematics Department are expected to have the equivalent of MATH 320 (Real Variables I), and MATH 321 (Real Variables II) as well as some elementary knowledge of ordinary and partial differential equations (e.g. MATH 215 (Elementary Differential Equations I) and MATH 316 (Elementary Differential Equations II)) and statistics (e.g. STAT 305 (Introduction to Statistical Inference)). Brief course descriptions can be found at MATH and STAT. Applicants are expected to be able to write computer code. The course CPSC 122 provides this skill. Applicants from non-anglophone countries must obtain a TOEFL score of at least 600 with a TWE score of 5.0. The GRE exam is not required. To apply to this program through the Mathematics Department go to its web page and follow the links "Prospective Students" and "Online Application". To apply through another department, contact that department.


    Students must take at least 30 credits of course work and write an essay.

    Core Courses

    (must be taken)
  • COMM 671 Theory of Finance,
  • COMM 673 Advanced Topics in Theoretical Asset Pricing,
  • MATH 605D Topics in Applied Mathematics - Mathematical Finance Theory
  • MATH 607D Topics in Numerical Methods - Stochastic Processes in Financial Applications.

  • In addition to these core courses, students can choose from the following courses and can design their program with a mathematical, computational, statistical focus or they may select a combination of courses from different focus areas.


    Statistical Focus

  • Capstone courses: STAT 543 Time Series Analysis; STAT 560/561 Statistical Inference
  • Other electives: STAT 530 Bayes Inference and Decision; STAT 538 Generalized Linear Models; STAT 541 Applied Multivariate Analysis;
  • Computational Focus

  • Capstone courses: CPSC 542 Topics in Numerical Computation: Nonlinear Optimization
  • Other electives MATH 521 Numerical Analysis; CPSC 517 Sparse Matrix Computation; CPSC 520 Numerical Solution of Differential Equations.
  • Mathematical Focus

  • Capstone courses: MATH 606 Topics in Differential Equations: Models from Mathematical Finance
  • Other electives Math 507 Measure Theory; Math 544/545 Probability
  • Multi-Agent Systems

  • Capstone courses: CPSC 532 Topics in AI: Multi-Agent Systems; CPSC 564 Data Mining
  • Other electives CPSC 500 Algorithms; CPSC 502 Artificial Intelligence; CPSC 504 Data Management; CPSC 540 Machine Learning.
  • Economics and Finance

  • Economics : ECON 527 Econometric Methods; ECON 590A Advanced Topics in Economics;
  • Finance COMM 583 Forecasting/Time Series in Business Environments; COMM 586; COMM 674 Advanced Topics in Empirical Asset Pricing; COMM 695 Advanced Topics in Empirical Corporate Finance; COMM 612 Advanced Optimization; COMM 616 Optimization Theory and Applications


    (must be taken if equivalent course not taken previously )
  • Microeconomics such as ECON 500,
  • Probability at the level of MATH 418,
  • Stochastic Processes such as MATH 419.
  • Numerical Methods for Differential Equations such as Math 607E.
  • Statistics prerequisites in regression and time series analysis may be required for courses below.

  • Additional Program Information

    Students registered in the Finance Division may choose some MBA modules as Electives.
    Students registered in Mathematics will follow the program under the auspices of the Institute of Applied Mathematics. The IAM Graduate Student Handbook provides useful information on requirements.
    The complete program must be approved by a program advisor.

    Participating Mathematics Faculty

  • Martin Barlow
  • Ivar Ekeland
  • Ulrich Haussmann
  • Rachel Kuske
  • John Walsh
  • Participating Finance faculty include Ali Lazrak and Tan Wang.