Mathematical & Computational Finance (MS)

Objectives

The M.S in Mathematical and Computational Finance provides students with the theoretical knowledge as well as the practical methods and skills needed to begin or enhance careers as quantitative analysts in the financial industry. The program aims to provide the multidisciplinary foundations preparing quantitative analysts for this life-long development of skills and understanding.

We expect that, as a student and/or graduate of the M.S. in Mathematical and Computational Finance program, you will exhibit the following:

• Professionalism: Our students will develop professional collaboration, communication, and project management skills required for senior positions in industry, financial, investment, banking and insurance industries.
• Academic Excellence: Our students are dedicated to building an academic foundation that bridges the critical intersection of mathematics, technology, and finance.
• Commitment to Growth and Development: Because of the evolving nature of financial markets and institutions, students of the field must be ready to learn new ideas and methods across a broad range of disciplines including mathematics, statistics, computational science, finance, and economics.

Program Summary

• Degree Awarded: Master of Science in Mathematical and Computational Finance
• Credits required: 33 (11 three-credit hour courses)
• Program Objective: To prepare students in quantitative modeling of financial markets/instruments and analysis of those models to obtain information of practical value in the financial industry.

MSMCF: Core Courses

• Fin 641 - Derivative Markets
• Math 611 - Numerical Methods for Computation
• Math 605 - Stochastic Calculus
• Math 646 - Time Series Analysis
• Math 604 - Mathematical Finance
• Math 606 - Term Structure Models
• Math 666 - Simulation for Finance
• Math 608 - Partial Differential Equations for Finance
• Math 607 - Credit Risk Modeling
• Math 609 - Project in Math & Computational Finance

Applied Quantitative Finance Option: Core Courses

• PTC 601 - Advanced Professional and Technical Communication
• MATH 604 - Mathematical Finance
• MATH 605 - Stochastic Calculus
• MATH 606 - Term Structure Models
• MATH 607 - Credit Risk Models
• MATH 608 - Partial Differential Equations for Finance
• MATH 609 - Projects in Mathematical and Computational Finance
• MATH 611 - Numerical Methods for Computation
• FIN 641 - Derivatives Markets
• MATH 666 - Simulation for Finance
• MGMT 641 - Global Project Management

How can I find out more?

• MSMCF Program Guide
• Attend a graduate student open house.
• Request information from our Admissions Office.

Learning outcomes

The M.S. in Mathematical and Computational Finance (MSMCF) provides students with the mathematical and computational tools, as well as the understanding of financial instruments and markets needed to obtain positions as quantitative analysts in financial institutions, including Wall Street investment firms. While students will take away a range of practical skills and theoretical knowledge from their study, the specific learning outcomes expected of graduates from the M.S. in Mathematical and Computational Finance program include:

• Ability to apply knowledge of mathematics and mathematical methods to the pricing and hedging of financial derivative securities.
• Ability to identify well-defined features of quantifiable systems.
• Ability to formulate a mathematical model of a quantifiable system.
• Ability to use mathematics to solve a mathematical model or problem. In particular, an ability to extract quantitative data and information from a mathematical model.
• Ability to distinguish between a good (or well-founded) mathematical model and a bad or (poorly-founded) model.
• Ability to communicate effectively. In particular, an ability to communicate concepts and methods of applied mathematics, and their relation to problems in other science and engineering disciplines.
• Ability to work effectively, both independently and as part of an interdisciplinary group.
• A recognition of the need for and an ability to engage in lifelong learning.