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Mathematical Finance 643
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  Graduate School-New Brunswick 2017 Programs, Faculty, and Courses Mathematical Finance 643 Requirements  

Requirements


Courses

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, and statistics.

Required Courses

Mathematics

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

Economics

16:220:507 Econometrics I

16:220:508 Econometrics ll

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.

Mathematics

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: 16:642:573, 621. Corequisite: 16:642:622.

16:642:625 Portfolio Theory and Applications (3)
Introduction to modern quantitative portfolio management, from theoretical foundations to the advanced applications, emphasizing models and mathematical, numerical, and statistical techniques.
Prerequisites: 16:642:621, 16:220:507. Corequisite: 16:220:508.

16:642:626 Fixed-Income Securities and Derivative Modeling (3)
Fixed-income securities products; interest rate and yield curve models; models for fixed-income pricing and risk management; exotic fixed-income derivative modeling; mortgage-backed securities; stochastic volatility models.
Prerequisites: 16:642:573, 621. Corequisite: 16:642:622.

16:642:627 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, 16:220:507. Corequisite: 16:220:508.

16:642:628 Topics in Mathematical Finance (3)
Topics rotate from semester to semester and year to year. Recent topics have included (a) Energy Risk, Commodities, and Derivative Modeling, (b) Fixed-Income Products and Derivative Modeling, and (c) Quantitative Risk Management.
Prerequisite: Permission of mathematical finance program director.

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 master of science 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 master of science degree in mathematics.
Prerequisite: Permission of mathematical finance program director.

Statistics

16:960:567 Applied Multivariate Analysis

16:960:583 Methods of Statistical Inference

16:960:588 Data Mining

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

Finance

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

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

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

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

 
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