Master of Mathematical Finance
Admission Requirements
Admission to the Master of Mathematical Finance program requires a bachelor’s degree in a quantitative discipline such as mathematics, quantitative finance, engineering, or statistics with a minimum cumulative GPA of 3.0/4.0. Applicants are required to have a background in undergraduate-level probability theory, multivariate calculus, and linear algebra. Background in ordinary differential equations will enhance the chance of admission to the program. If required, TOEFL scores should be a minimum of 90/250 (internet-based/computer-based test score) or the IELTS score should be a minimum of 6.5. A professional statement of goals/objectives (two pages) and a curriculum vitae must be submitted. Two letters of recommendation are required (at least one must be from academia). An interview may also be required.
Typically, admitted students score at least 156 on the quantitative portion of the GRE and at least 3.0 on the analytical writing portion. However, meeting the minimum or typical GPA test score requirements does not guarantee admission. GPA and test scores are just some of several important factors considered for admission to the program, including grades in mathematics courses, letters of recommendation, and the student’s overall record of achievements.
Curriculum
Code | Title | Credit Hours |
---|---|---|
Core Courses | (21) | |
MSF 505 | Futures/Option/OTC Derivatives | 3 |
or MSF 524 | Models for Derivatives | |
MATH 527 | Machine Learning in Finance: | 3 |
MATH 542 | Stochastic Processes | 3 |
MATH 548 | Mathematical Finance I | 3 |
MATH 565 | Monte Carlo Methods in Fin | 3 |
MATH 582 | Mathematical Finance II | 3 |
MATH 588 | Advanced Quant Risk Mgmt | 3 |
Applied Mathematics and CS Elective Courses | (6) | |
Select a minimum of two courses from the following: | 6 | |
Advanced Data Mining | 3 | |
Partial Differential Equations | 3 | |
Mathematical Modeling | 3 | |
Probability | 3 | |
Stochastic Analysis | 3 | |
Stochastic Dynamics | 3 | |
Stochastic Partial Diff Equatn | 3 | |
Introduction to Time Series | 3 | |
Multivariate Analysis | 3 | |
Adv Design of Experiments | 3 | |
Statistical Learning | 3 | |
Computational Mathematics I | 3 | |
Computational Mathematics II | 3 | |
Complexity of Numerical Prob | 3 | |
Math for Algorithmic Trading | 3 | |
Ther&Prac Fixed Income Modelng | 3 | |
Thry/Prac Modlng&Crdt Deritvs | 3 | |
Num Meth for Partial Diff Equa | 3 | |
Meshfree Methods | 3 | |
Finance Elective Courses | (3) | |
Select a maximum of one course from the following: | 3 | |
Models for Derivatives | 3 | |
Term Struc Mod & Int Rate Der | 3 | |
Computational Finance | 3 | |
Struct Fixed Income Portfolios | 3 | |
Quant Investment Strategies | 3 | |
Market Risk Management | 3 | |
Credit Risk Management | 3 | |
Time Series Analysis | 3 | |
Bayesian Econometrics | 3 | |
.NET and Database Management | 3 | |
C++ with Financial Markets | 3 | |
OOP & Algorithmic Trading Sys | 3 | |
High Frequency Finance | 3 | |
Equity & Equity Deriv Trading | 3 | |
FOREX & Fixed Income Strat | 3 | |
Total Credit Hours | 30 |
Core Requirement
All mathematical finance students must complete seven core classes unless they have obtained written permission from their academic adviser to substitute an alternative class for a core class.
Course Substitutions
To the extent that students have completed commensurate coursework or professional experience, substitutions to the required curriculum may be permitted, with the approval of the academic adviser.
Transfer Credit
Students may also transfer up to two classes from a graduate program at another accredited university if the student has not used the classes to satisfy the requirements for a degree at the previous university. Additional classes may be transferred with the permission of the program director.
Prerequisite Courses
Some students may be required to take prerequisite courses in mathematics, statistics, or computer programming before being admitted to a graduate course.