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  Graduate School–New Brunswick 2010–2012 Programs, Faculty, and Courses Mathematical Finance 643 Requirements  



For descriptions and prerequisites, please see the Rutgers Business School: Graduate Programs-Newark and New Brunswick  catalog for finance courses and the appropriate sections of the Graduate School–New Brunswick catalog for courses offered by the graduate programs in computer science, economics, electrical and computer engineering, mathematics, operations research, and statistics.

Required courses


16:642:573,574  Numerical Analysis I,II, or

16:642:575  Numerical Solution of Partial Differential Equations

16:642:621,622  Mathematical Finance I,II

16:642:630  Seminar in Mathematical Finance


16:960:563  Regression Analysis

16:960:565  Applied Time Series Analysis

Elective courses and selected course descriptions

Subject to approval by the mathematical finance program director, students can replace one or more of the electives listed here with graduate courses offered by Rutgers Business School or the graduate programs in computer science, economics, electrical and computer engineering, mathematics, operations research, or statistics.


16:642:623  Computational Finance (3)
Implementation of models for pricing and hedging derivative securities, using C++ programming projects, with emphasis on Monte Carlo simulation, finite difference solution of partial differential equations, binomial and trinomial trees, and the fast Fourier transform (FFT).
Prerequisites: 16:332:503,16:642:573, 621. Corequisites: 16:642:574 or 575, 622.

16:642:624  Credit Risk Modeling (3)
Single name credit derivatives; structural, reduced form or intensity models; credit default swaps; multiname credit derivatives; top down and bottom up models; collaterized debt obligations; tranche options; risk management.
Prerequisites: 16:642:622 and one of 16:642:573,574, or 575.

16:642:625  Portfolio Theory and Applications (3)
Introduction into modern quantitative portfolio management, from theoretical foundations to the advanced applications, emphasizing models and mathematical, numerical, and statistical techniques.
Prerequisites: 16:642:621, 16:960:563. Corequisite: 16:960:565.

16:642:627  High-Frequency Finance and Stochastic Control (3)
Introduction to mathematical models useful in understanding and developing automated trading systems; Glosten-Milgrom, Roll, and Kyle models; nature of high frequency data; stochastic control and the Hamilton-Jacobi-Bellman equation.
Feehan, Ocone, Cushman
Prerequisites: 16:332:503, 16:642:621, 16:960:563, 16:960:565 or equivalent.

16:642:628  Topics in Mathematical Finance: High-Frequency Finance and Stochastic Control (3)
An introduction to stochastic control and estimation with emphasis on the Hamilton-Jacobi-Bellman equation, Kalman filtering, and applications to high-frequency finance and trading.
Prerequisites: 16:332:503, 16:642:621, 16:960:563. Corequisite: 16:960:565.

16:642:628  Topics in Mathematical Finance: Interest Rate Derivative Modeling (3)
Fixed-income instruments. Spot and curve interest rate models, including Cox-Ingersoll-Ross, Hull-White, SABR, and Vasicek short rate models, Heath-Jarrow-Morton term structure model. Calibration of models against market data.
Prerequisites: 16:642:573, 621. Corequisite: 16:642:622.

16:642:629  Special Research Projects in Mathematical Finance (1)
Research project performed in connection with the master's essay for the mathematical finance option of the M.S. degree in mathematics, often as part of an industry internship in quantitative finance.
Prerequisite: Permission of mathematical finance program director.

16:642:630  Seminar in Mathematical Finance (0.5)
Seminar in mathematical finance theory, industry practice, and career preparation for students pursuing the mathematical finance option of the M.S. degree in mathematics.
Prerequisite: Permission of mathematical finance program director.


16:960:567  Applied Multivariate Analysis

16:960:583  Methods of Statistical Inference

Computer Science

16:198:541  Database Systems

Electrical and Computer Engineering

16:332:503  Programming Methodology (C++) for Numerical Computing and Computational Finance (3)
Fundamentals of object-oriented programming and C++ with an emphasis on numerical computing and computational finance applications. Topics include program structure and C++ syntax (loops, functions, arrays, pointers); objected-oriented concepts (abstract data types, classes, overloading, inheritance), and mathematical functions; numerical methods; and quantitative finance applications.
Prerequisite: Introductory programming course.

16:332:566  Parallel and Distributed Computing

16:332:567  Software Engineering

16:332:569  Database System Engineering


22:390:601  Risk and Insurance Management
Prerequisite: 16:642:621 and permission of Rutgers Business School.

22:390:603  Investment Analysis and Management
Prerequisite: 16:642:621 and permission of Rutgers Business School.

22:390:608  Portfolio Management
Prerequisite: 16:642:621 and permission of Rutgers Business School.

22:390:611  Analysis of Fixed Income Securities
Prerequisite: 16:642:621 and permission of Rutgers Business School.

For additional information, contact RU-info at 732-445-info (4636) or
Comments and corrections to: Campus Information Services.

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