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M.S. in Applied Mathematics with a Specialization in Quantitative Risk Management

The Quantitative Risk Management specialization trains you for a career in the quantitative financial or insurance industries, or for a Ph.D. program geared towards the mathematical aspects of these disciplines. You will acquire knowledge in the fundamentals of financial risk management, as well as advanced pricing and hedging methodologies relevant to modern financial markets. You will be able to take a variety of courses in risk management, mathematical finance, artificial intelligence, stochastic analysis, statistics, and computational finance. 

Students must take MATH 540 or MATH 475, or show evidence of having taken a course in Probability equivalent to MATH 475.

The following two course options are required:

Required to take at least one of the following courses

  • MATH 582 Mathematical Finance II
  • MATH 565 Monte Carlo Methods in Finance
  • MATH 587 Theory and Practice of Modeling Risk and Credit Derivatives

Remaining Elective courses to be chosen in consultation with your academic advisor, or from the following list, or any unused core/required courses listed above:

PLANS OF STUDY

Here we present a few plans of study for the various options in the MS program. Note that Math 593, a required course, is not listed below under the plans of study as it is a zero credit course offered every semester.

A Sample Course Sequence for the Specialization in `Computational Statistics for Data Science’ with Project:

Fall - Year 1

Math 577
Math 540 or Math 475
Math 542



3 credit hours
3 credit hours
3 credit hours

Spring - Year 1

Math 588
Math 582
Math 591



3 credit hours
3 credit hours
1-3 credit hours

Fall - Year 2

Core Math 500/553/563
Elective
Math 591



3 credit hours
3 credit hours
1-3 credit hours

Spring - Year 2

Elective
Math 591



3 credit hours
1-3 credit hours
Total  32 credit hours