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4. 主要课程

Curriculum
The program consists of 48 credits (39 core and 9 elective) and can be taken on either a full-time basis to be completed in two years (not including summer sessions) or a part-time basis to be completed in four years (not including summer sessions). An illustrative schedule of the course offerings for each option is shown here (pdf).  All students must also take the non-credit Introduction to Finance course offered during the orientation week, and all full-time students must take the non-credit Fundamentals of Career Planning course.

Core Courses

Applied Stochastic Processes (26:960:580)
Econometrics (26:220:507)
    or Simulation & Modeling for Engineering & Business (NJIT CS661)
Financial Institutions & Markets (22:390:604)
Financial Modeling I (22:839:571)
Financial Modeling II (22:839:662)
Fundamentals of Career Planning (22:135:583)
Introduction to Finance (Course # TBD)
Introduction to Probability (26:960:575)
Investment Analysis & Management (22:839:603)
Microeconomics (26:220:501)
Numerical Analysis (22:839:510)
Object Oriented Programming in Finance I (22:839:614)
Object Oriented Programming in Finance II (22:839:615)
Operations Research Models in Finance (26:711:685)
Options (22:390:609)

Elective Courses

Advanced Econometrics (26:223:655)
Advanced Financial Management (22:390:605)
Analysis of Fixed Income Securities (22:390:611)
Applied Portfolio Management (22:390:658)
Credit Derivatives (16:642:611)
Empirical Finance (26:390:668)
Financial Management (22:390:587)
Financial Statement Analysis (22:390:613)
International Capital Markets (22:390:606)
Investment Banking (22:390:654)
Portfolio Management (22:390:608)
Risk Management (22:390:670)

5. 课程介绍

Core CoursesThe descriptions below briefly outline the core courses.



Applied Stochastic Processes (26:960:580)
This course reviews probability theory with emphasis on conditional expectations, Markov process, Poisson process, continuous-time Markov chains, renewal theory, martingale theory and stochastic calculus such as Ito's lemma, Browian motion, and related topics. (Pre-requisite: 16:960:582 or equivalent)




Econometrics (26:220: 507)
Statistical techniques for the analysis of models applicable to economic data and their application to management problems.



Financial Institutions & Markets (22:390:604)
Presents a detailed overview of the theory and institutional features of the U.S. financial system. Provides a comprehensive review of U.S. financial markets. Covers a survey of flow-of-funds data and U.S. financial markets and institutions, capital market theory, financial factors and economic activity, theory of the level and structure of interest rates. Prerequisites: 223:581 or 223:521; 223:591 or 223:520; and 390:587 or 390:522.



Financial Modeling I (22:839:571)
This course is the first of the two-course sequence in financial theory for Ph.D. and MQF students. The course surveys the fundamental assumptions and the analytical techniques of the modern finance theory. It builds a foundation for the study of higher-level courses in investment theory and corporate finance. Topics include capital market equilibrium models, risk analysis using utility theory, state preference theory, portfolio selection, market efficiency, and empirical tests of asset pricing models.



Financial Modeling II (22:839:662)
This course covers continuous time finance, similar to an advanced Ph.D. course in asset pricing.
It follows Financial Modeling I which covers discrete time finance and continues with continuous time financial theories. Topic-wise, it covers basic theories (backward and forward equations, change of measure, state pricing, arbitrage pricing, martingales), derivatives pricing (Black-Scholes model, Heston model, Geske model, Merton-Rabinovitch model), term structure of interest rates (Vasicek model, CIR model, HJM model, Hull-White model), multi-factor models (Chen-Scott model, Bakshi-Cao-Chen-Scott model, Duffie-Pan-Singleton model), credit derivatives (Jarrow-Turnbull model, Duffie-Singleton model) and some numerical methods (binomial model, finite difference methods, Monte-Carlo).
Interested students can get a good idea from the following books: Merton – Continuous Time Finance, Duffie - Dynamic Asset Pricing Theory, Ingersoll - Theory of Financial Decision Making, and similar others.



Fundamentals of Career Planning (22:135:583)
These seminars are designed to provide students with an overview of the services offered by the Office of Career Management (OCM). It will also introduce students to the Rutgers Business School’s Career Development Program (CDP), including a presentation focused on business etiquette essentials and a timeline of scheduled events.



Introduction to Finance (Course # TBD)
The course will focus on key concepts in Finance such as the time value of money, the relationship between risk and return, and asset pricing / valuation theories. In addition, some practical institutional knowledge will be discussed.




Introduction to Probability (26:960:575)
This course covers set theory, sample spaces, events, probability functions on sample spaces, combinatorial methods, conditional probability, Bayes' theorem, Markov chains (if time permits), random variables and distributions (discrete, continuous, mixed, multivariate), conditional distributions, functions of random variables, expectations (mean, variance, covariance, correlation, moments, conditional expectations), moment-generating functions, inequalities (Chebyshev, Jensen), limit theorems (laws of large numbers, central limit theorem), large sample approximations (Poisson and normal to binomial, normal to Poisson, normal to the t- distribution, etc.), special distributions (Bernoulli, binomial, multinomial, geometric, negative binomial, hypergeometric, Poisson, exponential, gamma, beta, t, normal and multivariate normal, and chi-square.



Investment Analysis & Management (22:390:603)
Provides overview of the fields of security analysis and portfolio management. Introduces the analysis of individual investments with special reference to common stock. Covers nature of financial markets, security pricing models, critiques of techniques of security analysis. Introduces problems of portfolio selection. Designed for the finance major who is interested in the security/investment area as a possible career.




Microeconomics (26:220:501)
These courses survey and apply consumer theory, theory of the firm, decision making under uncertainty, elements of marginal analysis, risk analysis to problems in demand analysis, production, cost, market structure, pricing, and an introduction to non-cooperative game theory with applications to economic problems with asymmetric information.





Numerical Analysis (22:839:510)
This course derives, analyzes, and applies methods used to solve numerical problems with computers; solution of linear and nonlinear algebraic equations by iterations, linear equations and matrices, least squares, interpolation and approximation of functions, numerical differentiation and integration, and numerical solutions of ordinary differential equations.



Object Oriented Programming in Finance I (22:839:614) & II (22:839:615)
C++ is a higher level computer language with multiple personalities. The objective for this two part course is for the student to become proficient in C++ programming so as to be able to develop c++ functions and classes for independent and interrelated economic models via parametrization and/or class interrelation. Topics will include data structures from the simple data types and matrices to interrelated classes and inheritance; standard mathematics libraries, logic and processing from simple conditionals to iteration and multitasking and the various forms of parametrization.

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