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New York University - MSc Mathematics in Finance

Discuss In Forums || Updated Oct 2009

New York University - MSc Mathematics in Finance
New York, NY, United States
Program Contacts: This e-mail address is being protected from spambots. You need JavaScript enabled to view it

The Summary:

The Courant Master of Science Program in Mathematics in Finance is a professional master’s program. It has a strong pragmatic component, including practically oriented courses and student mentoring by finance professionals. Our graduates know more finance than most science graduates and have stronger quantitative skills than most business graduates. They start with undergraduate degrees in quantitative subjects such as mathematics, physics, or engineering. They are admitted to the program through a highly selective process. Here at courant, they experience a tightly integrated curriculum that provides an efficient introduction to the theoretical and computational skills that are genuinely used and valued in the industry. Our program’s special strengths include:

Course Structure/Topics:

The Mathematics in Finance Masters Degree Curriculum consists of 12 courses — 11 one-semester lecture courses, and the Project and Presentation class, otherwise known as the Master’s Project. The curriculum has five major components:

  • Financial theory and modeling
  • Mathematical tools
  • Financial applications
  • Computational skills
  • Practical training

Financial theory and modeling. This component forms the theoretical core of the program, covering topics ranging from binomial trees to Black-Scholes to Heath-Jarrow-Morton. Courses within this component are Derivative Securities and Continuous Time Finance.

Mathematical tools. These classes provide mathematical background, covering topics such as the Brownian motion and the Ito calculus, statistical analysis of financial data, and the relation between diffusions and partial differential equations. Courses within this component are Stochastic Calculus, Partial Differential Equations for Finance, and Time Series Analysis and Statistical Arbitrage.

Financial applications. These classes are taught by industry specialists from prominent New York financial firms. They emphasize practical aspects of financial mathematics, drawing on the instructor’s experience and expertise. Particular emphasis is devoted to trading and hedging strategies. Courses within this component are Risk and Portfolio Management with Econometrics, Advanced Risk Management, Financial Engineering Modles for Corporate Finance, Interest Rate and Credit Models, and Case Studies in Financial Management.

Computational skills. These classes provide students with a broad range of software skills, and facility with computational methods such as optimization, Monte Carlo simulation, and the numerical solution of partial differential equations. Courses within this component are Computing in Finance, Scientific Computing, and Computational Methods for Finance.

Practical training. In addition to course work, each student does a Masters Project. Most projects are done in groups, mentored by finance professionals. Students address practical quantitative problems from first formulation to final presentation, making full use of their modeling and computing skills. Here are examples of project topics by previous students.

The boundaries between these components are not rigid. For example, the Statistics and Econometrics class is quite practical and the Case Studies in Financial Modeling course has a strong theoretical component.  Click here for more details on the degree requirements

During the summer between the 2nd and 3rd semesters, students are expected to find internships at financial institutions. Internships provide valuable experience to put into practice the theoretical knowledge learned in the classroom and often an entrée into the field. Many students continue working part-time at the conclusion of the internship, obtain a full-time offer, and/or do their Master’s project with a supervisor at their place of internship.

Key Stats:

Acceptance Rate:
Annual Intake: 30 (Fall intake)
Application Deadline: March 1 (Target deadline)
Average Age at Entry: 26
Average Years of Work Experience of Class:
Dissertation/Thesis: yes
Duration of Program: 3 terms (1 Year)
Entry Requirements:
* Multivariate calculus (through partial derivatives, multiple integrals, and Taylor series)
* Linear algebra (systems of equations, determinants, factorization, range and null space, and eigenvalues of symmetric matrices)
* Calculus-based course in probability (independence, conditional probabilities, Gaussian distribution, law of large numbers, central limit theorem).
--- GMAT - not accepted
GMAT: Average - Not Accepted
GPA: Average -
International Students: 50%
Placement Rate:
Required Courses for Completion: 12 courses (36 credits)
Student-Teacher Ratio:
Tuition (2009-10): $1,196 per credit.

Additional Information:

Notable faculty include Steve Allen, Marco Avellaneda, Peter Carr, Peter Fraenkel, Nassim Taleb, Bruno Dupire, Ali Hirsa, Jim Gatheral.

Fellows and advisory board include Ali Hirsa, Craig Friedman, Iraj Kani, Raymond Iwanowski, Emanuel Derman, Harry Markowitz


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