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
Mathematics16:642:573,574
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.
