M.S. Statistics Degree with Specialization in Computational Finance

The M.S. in Statistics with Specialization in Computational Finance (MS CF) is a highly interdisciplinary program involving course offerings from different academic departments. The goal of the program is to equip students with the tools necessary to pursue a career in a quantitative financial field. The 2-year course work provides students with comprehensive and practical knowledge of the mathematical, statistical, and computational skills needed for the creation, implementation, and evaluation of the models and products used by the financial sector to manage risk and develop investment strategies. Internship, career fairs, and recruiting programs at Purdue provide students with great opportunities before and upon graduation.

Employment Perspectives

Quantitative and computational finance is a field with enormous impact, and excellent employment opportunities. The MS CF program is designed to prepare students for a wide range of careers both inside and outside the financial industry. Companies recruiting our graduates include:

  • Investment banks and trading companies
  • Asset management firms and pension funds
  • Insurance companies
  • Financial software and consulting firms
  • Energy companies

Expanding alumni network with top students landing jobs on Wall Street, in Chicago, and other important financial centers. Sample positions: equity trading -”Quant”, quantitative analyst, mathematical finance modeler, fixed-income researcher, investment consultant, risk analyst, and financial product design.

Course work

The core courses in the MS CF program go beyond the generalities of financial models and products, and provide a thorough understanding on the quantitative aspects of

  • Arbitrage pricing of derivatives in equity, fixed income, and credit markets
  • Portfolio management and CAPM
  • Key financial algorithms of option pricing, optimization, simulation, and calibration (with programming in C++, C#, MATLAB, and VBA)
  • Statistical methodologies including Multivariate Data and Time Series Analysis with computational experience in SAS and R

Elective courses offered by Krannert School of Business complement the curriculum with a more pragmatic general approach of the products and daily practices of the market. Elective courses include Options and Futures, Portfolio Management, Risk Management, and Econometrics.

Course Requirements

The requirements for the Master's degree in Statistics with specialization in Computational Finance are typically completed in two intensive years. The resulting MS Statistics degree includes additional courses in mathematical and investment finance, and computational science.

The courses comprising the 34 required credits for the Master's degree in statistics with emphasis in computational finance are divided into three groups.

  1. Required Stat Courses (15 cr.)

    Probability STAT 51900
    Mathematical Statistics STAT 52800
    Time Series STAT 52000
    Intermediate Statistical Methodology STAT 52500
    Advanced Statistical Methodology STAT 52600
  2. Required Core Computational Finance courses. (16 cr.)

    Mathematics of Finance (STAT 54000)

    Adv. Probability, Options, and Num. Methods (STAT 54100)

    Simulation Design and Analysis (IE 58100) or Introduction to Computational Statistics (STAT 545)

    7 or more credit hours approved by the CF committee from the following list:

    Options and Futures MGMT 64100 (2 cr.)
    Security Analysis MGMT 64200 (2 cr.)
    Financial Risk Management MGMT 64300 (2 cr.)
    Portfolio Management MGMT 61400 (2 cr.)
    Spreadsheet Modeling and Simulation MGMT 690S/57000 (2 cr.)
    Seminar in Financial Markets MGMT 61600 (3 cr.)
    Seminar in Financial Markets MGMT 61700 (3 cr.)
    Design and Analysis of Financial Algorithms STAT 598W (3 cr.)
    Venture Capital And Investment Banking MGMT 64400 (2 cr.)
    Financial Management I MGMT 61000 (3 cr.)
    Financial Modeling with Jump Processes STAT 598F (3 cr.)
    Financial Time Series STAT 598K (3 cr.)

    Other relevant information: Policy for taking Krannert/Management classes (pdf)

  3. Elective courses (3 cr.)

    3 or more credit hours of courses related to CF and approved by the CF committee. These can be courses from any department or school. The CF advisor will help students make a selection.

    Possible departments to choose from include:

    Management, Finance, Economics, Statistics, Computer Science, Agricultural Economics & Industrial Engineering

    Possible topics include:

    • advanced finance seminar
    • portfolio management
    • security analysis
    • international monetary problems
    • financial time series
    • Bayesian statistics in finance
    • Monte-Carlo methods

    Note: Other courses approved by the Statistics Department Graduate Committee can be substituted for courses that have been taken previously. The final transcript should include at least five statistics courses aside from the STAT courses in Group II.

    A typical degree plan for the MS degree in Statistics with CF specialization will look like this:

Ph.D. in Statistics with research emphasis on applications to finance

The Department of Statistics offers the Ph.D. for original research in probability or statistics. The research emphasis may be directed toward applications in finance with the concurrence of the major professor. See the description of the Department of Statistics Ph.D. Program. Professor F. G. Viens may be contacted for more details.

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Last Updated: Oct 2, 2017 2:34 PM

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