## Master of Science in Mathematics - Computational Finance Option

This is a Master of Science degree especially designed to train students with strong mathematics backgrounds in up-to-date mathematical and computational skills in quantitative finance and insurance. Such training is intended to produce high caliber individuals who can confidently undertake interdisciplinary research and analysis in modern financial risk management. The focus will be in preparing talented individuals to face the quantitative and computational challenges in financial service and insurance sectors.

In order to achieve these goals the program requires:

- a solid training in Financial Mathematics, Optimization, Stochastic Simulation; a broad background in the areas of Finance and Insurance, Numerical Analysis, and Statistical Analysis
- practice in both professional written and oral communication
- both group and individual projects
- a strong computing component

Departmental requirements and regulations for the MS in Computational Finance are specified below. The regulations of the Graduate School for master's programs are available in the Graduate School Policies and Procedures Manual (http://www.gradschool.wsu.edu).

##### Prerequisites

All graduate students are expected to have a background in mathematics equivalent to that provided by our undergraduate degree. Ideally, this would include familiarity with the material covered in Math 401 and 402, and Math 420 and 421, and some experience with computer programming. Students with a deficient background are expected to make up these deficiencies at the earliest opportunity.

##### Course and Hours

A candidate must complete at least 31 semester hours of course work. This includes a core consisting of:- Math 464 or Math 564, Optimization
- Math 516 or Stat 536, Simulation
- Math 575, Asset Pricing in Financial Engineering
- Math 576, Quantitative Risk Management

__and__at least two additional graduate level courses from the following finance courses:

- Fin 521 (Interest Rates and Financial Markets)
- Fin 526 (Problem in Financial Management)
- Fin 527 (Investment Analysis)
- Fin 528 (Portfolio Management)
- Fin 581 (International Finance)

__and__at least three additional graduate level courses from the following math and statistics courses:

- Math 545 (Numerical Analysis of Evolution Equations)
- Math 548 (Numerical Analysis)
- Math 565 (Nonlinear Optimization)
- Stat 523 (Statistical Methods)
- Stat 516 (Time Series)
- Stat 519 (Applied Multivariate Analysis)

##### Transfer Credit

Up to eight hours of transfer credit may be given for suitable course work done elsewhere.

##### The Program of Study

A Program of Study must be submitted by the deadlines indicated in Section 3 of the Math Department's Graduate Student Handbook (http://www.math.wsu.edu/info/hb.pdf). It is, however, suggested that this be done in the second semester of graduate work. The appropriate form is available at the Graduate School Office or may be downloaded from its web site.

##### The MS Examination

Each MS student must pass a final oral examination that covers all of the student's course work, and includes an oral presentation on the results of the student's Math 702 individual project (see below). This examination may be scheduled when all requirements of the Department and the Graduate School have been satisfied (or are expected to be satisfied by the end of the current semester). The deadlines for scheduling this examination are indicated in Section 3 of the Math Department's Graduate Student Handbook. The student's advisory committee will conduct this examination.

##### The Application for Degree

An approved Program of Study must be on file in the Graduate School before the Application for Degree may be filed. Candidates may not schedule a final examination until an Application for Degree has been filed.

##### Thesis

There is no thesis requirement. However, a student must take four hours of Math 702 that must involve the completion of an individual project. The topics of individual projects include, for example, analysis of financial time series data, pricing of financial derivatives via simulation, asset allocation optimization, or formulation of a solution to the problem encountered during a summer internship. The individual project should normally be completed by the end of the fourth semester of the student's work on the degree. The student's advisory committee, consisting of three mathematics faculty members, will supervise this project. A written project report should be submitted when the project is completed. The final MS examination must include an oral presentation by the student about the results of the project, with questions from the student's MS committee.

##### Computational Finance Faculty

- Hongbo Dong (PhD, University of Iowa, 2011, Mathematical Optimization, Convex Conic Optimization and Copositive Programming, Mixed Integer Nonlinear Programming, Optimization Modeling)
- Alan Genz (PhD, University of Kent, 1976, Numerical Integration, Multiple Integrals, Statistical Analysis)
- Mark Lesperance (MS, Kansas State University, 1991, Property and Casualty Actuarial Methods)
- Haijun Li (PhD, University of Arizona 1994, Probability, Stochastic Inequalities, Risk Analysis)
- V.S. Manoranjan (PhD, University of Dundee, 1982, Industrial Applications, Mathematical & Computer Modeling)
- Charles N. Moore (PhD, University of California-Los Angeles 1986, Analysis, Harmonic analysis, Partial Differential Equations, Probability Theory)
- Jave Pascual (PhD, Iowa State University 1997, Engineering Reliability, Survival Analysis, Failure-Time Models and Data Analysis)
- Rocio Sotomayer (PhD, University of Alberta, 2008, Probability Theory, Stochastic Control, Risk Management and Insurance)
- Hong-Ming Yin (PhD, Washington State University, 1988, Financial Engineering, Portfolio Management, Applied Mathematics)