Master of Quantitative Finance Curriculum

The program consists of 45 credits (30 core and 15 elective) and can be taken on either a full-time basis to be completed in three semesters (not including summer sessions) or a part-time basis to be completed in three years (not including summer sessions). 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.

MQF Internship is an integral and important enhancement to class lectures, readings, and student assignments. Internship provides students practical experience in the quantitative finance field with the opportunity to experience theory in the business environment. We strongly recommend students to seek part-time internship beginning with the first semester of the Program. In the final semester of the Program, students who need less than the full-time course load to complete the Program are permitted to obtain full-time internship.

 

Core Courses

Course # Title Cr
22:390:611 Analysis of Fixed Income Securities 3
26:220:507 Econometrics 3
22:390:604 Financial Institutions & Markets 3
22:839:571 Financial Modeling I 3
22:839:662 Financial Modeling II 3
22:839:664 Fundamentals of Career Planning P/F
22:839:510 Numerical Analysis 3
22:839:614 Object Oriented Programming in Finance I 3
22:839:615 Object Oriented Programming in Finance II 3
22:390:609 Options 3
26:711:563 Stochastic Calculus for Finance 3

Note: P/F stands for pass/fail. Students must complete this class satisfactorily.

 

Electives

Course # Title Cr
26:223:655 Advanced Econometrics 3
22:390:605 Advanced Financial Management 3
22:390:658 Applied Portfolio Management 3
16:642:624 Credit Derivatives 3
26:198:644 Data Mining 3
22:010:648 Decoding of Corporate Financial Communications 3
22:390:613 Financial Statement Analysis 3
26:960:576 Financial Time Series 3
22:390:681 Hedge Funds 3
22:390:606 International Capital Markets 3
26:960:575 Introduction to Probability 3
22:839:603 Investment Analysis & Management 3
22:390:654 Investment Banking 3
26:220:501 Microeconomics 3
26:711:564 Optimization Models in Finance 3
22:390:608 Portfolio Management 3
22:390:670 Risk Management 3
22:390:601 Risk & Insurance Management 3
26:960:580 Stochastic Processes 3
NJIT CS661 Systems Simulation 3
22:839:638 Internship/Research 1-3

Additional Notes

1. "Econometrics (26:220:507)", "Financial Time Series (26:960:685)" and "Systems Simulation (NJIT CS661)" are substitutable core courses. If a student takes one of them as a core course, the student can take the other(s) as elective.

2. "Financial Institutions and Markets (22:390:604)" and "Risk Management (22:390:670)" are substitutable core courses. If a student takes one of them as a core course, the student can take the other as an elective.

3. "Stochastic Calculus for Finance (26:711:563)" and "Stochastic Processes (26:960:580)" are substitutable core courses. If a student takes one of them as a core course, the student can take the other as an elective.

4. "Decoding of Corporate Financial Communications (22:010:648)" and "Financial Statement Analysis (22:390:613)" are substitutable elective courses. A student can take either one as an elective, but not both.

 

Course Descriptions

26:223:655 - (3 cr)
Advanced Econometrics

In this course students will develop advanced econometric tools and strategies for their use in empirical finance and economics research. In particular, the course will provide students with a working knowledge of asymptotic statistical methods and the application of these statistical concepts to study large-sample properties of estimators. These large sample results will be applied to linear and nonlinear in parameters generalized least squares (GLS) and maximum likelihood (ML) estimators. These results are extended to develop a nonlinear instrumental variables estimator, the generalized method of moments (GMM) and various asymptotic testing procedures are derived for this general modeling framework. Panel data, simultaneous equations, time-series, discrete dependent, limited dependent and duration models and their application are covered.

Prerequisites: Econometrics (26:220:507)

22:390:605 - (3 cr)
Advanced Financial Management 

Examines the problems faced by the corporate financial manager on the theoretical, analytical, and applied level. The impact of the financing decision upon the value of the firm is analyzed. Theoretical and analytical aspects of the capital budgeting decision. An analytical framework is presented to evaluate leasing, bond refunding, and mergers and acquisitions. Theories of corporate governance are discussed.

Prerequisites: This course requires student to have an accounting background. Registration requires instructor's written permission. 

22:390:611 - (3 cr)
Analysis of Fixed Income Securities

Explores the investment characteristics, pricing, and risk/reward potential of fixed-income securities. The securities covered include bonds---with and without embedded options; mortgages and mortgage-backed securities together with their derivatives such as collateralized mortgage obligations (CMO's), income-only (IO's) and principal-only (PO's) strips; interest rate swaps; and interest rate futures and option contracts. In addition, this course will explore the strategies for investing in portfolios of fixed-income securities.

Fall semester only

Prerequisites: Financial Mgt (22:390:587 or 22:390:522); and Investment Analysis & Mgt (22:390:603).

22:390:658 - (3 cr)
Applied Portfolio Management

The purpose of this course is to teach students how to create an actual portfolio that meets the needs of a client in a manner consistent with the investment philosophy of Graham, Dodd, and Buffett. The client (previously an individual, now the Rutgers University Foundation) wishes the portfolio to have a Value orientation with hedge fund characteristics (i.e., the portfolio has both Long and Short positions.) From an organizational standpoint, each student will serve as an analyst responsible for a particular sector or industry. Students will be required to write two comprehensive stock reports (one Long recommendation and one Short recommendation) and present their findings in front of the class. The course will be primarily conducted on an independent study basis with only a moderate number of in-class meetings. We will meet in a classroom setting approximately once every two weeks. Additional communication will be done via phone (e.g. conference calls) and email. All students must have a strong understanding of financial statement analysis in order to effectively participate in the class.

Prerequisites: Students must contact instructor directly for permission to take this course. Professor will individually select students for this class.  

16:642:624 - (3 cr)
Credit Derivatives 

In addition to equity, interest rates, FX, and commodity derivatives, credit derivatives play an increasingly important role in financial markets. The course will include a review of jump processes; the basic theory of single name credit derivative modeling; structural, reduced form or intensity models; credit default swaps; default correlation, multiname credit derivative modeling; top down versus bottom up models; basket credit derivatives; collaterized debt obligations; and tranche options. The goal of the course is to cover most of the material in "Credit Risk Modeling" by David Lando (Princeton University Press, 2004) or "Credit Derivatives Pricing Models" by Philipp Schonbucher (Wiley, 2004).

This course is for 2nd-year students only.

Prerequisites: Stochastic Calculus for Finance (26:711:563) and Options (22:839:609) and Analysis of Fixed Income (22:839:611)

26:198:644 - (3 cr)
Data Mining

The key objectives of this course are two-fold: (1) to teach the fundamental concepts of data mining and (2) to provide extensive hands-on experience in applying the concepts to real world applications. The core topics to be covered in this course include classification, clustering, association analysis, and anomaly/novelty detection. This course consists of about 13 weeks of lecture, followed by 2 weeks of project presentations by students who will be responsible for developing and/or applying data mining techniques to applications such as intrusion detection, Web usage analysis, financial data analysis, text mining, bioinformatics, systems management, Earth Science, and other scientific and engineering areas. At the end of this course, students are expected to possess the fundamental skills needed to conduct their own research in data mining or to apply data mining techniques to their own research fields.

This course is for 2nd-year students only.

22:010:648 - (3 cr)
Decoding of Corporate Financial Communications

Interpretation and in-depth analysis of reported financial data. The role of taxes and tax disclosures will be included in the class discussions. Some aspects of valuation will be discussed. Issues include reported numbers making sense; reporting choices made by the preparer/firm when other choices under GAAP are available; strategy of firms in their choice of financial information disclosures; comparison of financial information within and across industries; projection of key information variables like earnings or cash flows into the future; financial reporting information used to gauge the riskiness of firms; prediction of the probability of bankruptcy using financial data.

Prerequisites: This course requires student to have an accounting background. Registration requires instructor's written permission. 

Decoding of Corporate Financial Communications (22:010:648) and Financial Statement Analysis (22:390:613) are substitutable elective courses. A student can take either one as an elective, but not both.

26:220:507 - (3 cr)
Econometrics 

The purpose of this course is to develop basic econometric estimation and hypothesis testing tools necessary to analyze and interpret the empirical relevance of financial and other economic data. This requires developing statistical methods for estimation of population parameters and testing hypotheses about them using a sample of data drawn from the population distribution, under various assumptions regarding the true population relationship between the observable economic variables. Focus will be on the theoretical foundations of econometric analysis and strategies for applying these basic econometric methods in empirical finance and economics research. Topics covered include estimation and hypothesis testing using the classic general linear regression model, combining sample and non-sample information, dummy variables, random coefficients, multicollinearity, and the basics of large sample theory, non-spherical disturbances, panel data, systems of equations, time-series, and their application.

Fall semester only

Econometrics (26:220:507), Financial Time Series (26:960:685) and Systems Simulation (NJIT CS661) are substitutable core courses. If a student takes one of them as a core course, the student can take the other(s) as elective.

22:390:604 - (3 cr)
Financial Institutions & Markets

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.  

Fall semester only

Prerequisites:Waived for MQF students.

Financial Institutions and Markets (22:390:604) and Risk Management (22:390:670) are substitutable core courses. If a student takes one of them as a core course, the student can take the other as an elective.

22:839:571 - (3 cr)
Financial Modeling I

This is a quantitatively-oriented financial economics course for the Master of Quantitative Finance (MQF) students. The course covers the basic concepts and analytical techniques of modern portfolio theory and asset pricing. Topics include Fisher separation, risk analysis using expected utility theory, mean-variance analysis, capital asset pricing model, arbitrage pricing theory, state preference theory, consumption-based asset pricing, market efficiency, and empirical tests of asset pricing models.

Spring semester only

22:839:662 - (3 cr)
Financial Modeling II 

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.

Fall semester only 

Prerequisites: Financial Modeling I (22:839:571) and Stochastic Calculus for Finance (26:711:563)

22:390:613 - (3 cr)
Financial Statement Analysis 

Presents techniques for analyzing a firm's current and projected financial statements for the purposes of credit analysis, security analysis, and internal financial analysis. Topics covered include financial distress prediction, evaluation of short-term and long-term loan requests, the impact of accounting information on security returns, determinants of bond ratings and yields, and the reliability of historical and forecasted accounting data. A working knowledge of spreadsheet analysis is expected. Special emphasis is placed on acquiring data from printed and computer databases and an introduction to specialized online databases and the Internet.

Prerequisites: This course requires student to have an accounting background. Student must show proof of having taken at least one accounting course (e.g. a foundational accounting course shown on an undergraduate transcript would be sufficient.) Registration requires instructor's written permission. 

Decoding of Corporate Financial Communications (22:010:648) and Financial Statement Analysis (22:390:613) are substitutable elective courses. A student can take either one as an elective, but not both.

26:960:576 - (3 cr)
Financial Time Series

This course covers applied statistical methodologies pertaining to financial time series, with an emphasis on model building and accurate prediction. Completion of this course will equip students with insights and modeling tools to analyze real world financial and business time series. Students are expected to have basic working knowledge of probability and statistics including linear regression, estimation and testing from the applied perspective. We will use R throughout the course so prior knowledge of it is welcome, but not required.

Spring semester only

Econometrics (26:220:507), Financial Time Series (26:960:685) and Systems Simulation (NJIT CS661) are substitutable core courses. If a student takes one of them as a core course, the student can take the other(s) as elective.

22:839:664 - (3 cr)
Fundamentals of Career Planning

Guided through a series of lectures, discussions, individual and group activities, role-plays, and assignments designed to educate, develop, and assist you to successfully navigate the challenging MQF profession; from self-discovery to job search to career management. Participation in information sessions, mock interviews, and coaching session is essential.

This course provides tools necessary for you to take ownership of your career and give you the competitive advantage critical to achieve your career goals. All 1st-year, full-time students are required to satisfactorily complete this course.

Fall semester only

22:390:681 - (3 cr)
Hedge Funds

This course will provide students with a solid and working understanding of hedge funds.  The course will not only cover an overview of the hedge fund industry, but also provide students with a strong understanding of more than a dozen hedge fund strategies, including equity long / short, global macro, statistical arbitrage, merger arbitrage, convertible arbitrage, and fixed income arbitrage.  The course will make extensive use of Excel spreadsheets to model specific hedge funds strategies and will also include live instruction on using cutting-edge Internet resources. In my view, often the best way to learn is by doing, so students will also manage a simulated $1 million hedge fund portfolio and design and present a hedge fund investment strategy group project.

This course is for 2nd-year students only.

22:390:606 - (3 cr)
International Capital Markets 

Offers an understanding of the international financial structure and studies its impact on business and individuals in various nations. Topics include the study of the adjustment mechanism used by nations to solve balance of payments difficulties, the examination of international liquidity and the new techniques being developed to replace gold; and a brief look at the implications of these developments in guiding the international operations of banks, other financial institutions, and business firms.

26:960:575 - (3 cr)
Introduction to Probability 

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.

22:839:603 - (3 cr)
Investment Analysis & Management 

Provides overview of the fields of security analysis and portfolio management. Introduces the analysis of individual investments with special reference to common stocks and bonds. Designed for the finance major who is interested in the security/investment area as a possible career.

22:390:654 - (3 cr)
Investment Banking 

This course covers the effective integration of financial theory and practice and explores the rapidly evolving theory of finance as it relates to a corporation's investment in assets and finance. We will also cover financial analysis and reasoning applied to problems faced by management. Topics include: mergers and acquisitions, leasing, project finance, the art of negotiating, securities industry, and financial engineering. Caricom, Aesean, and examine attempts elsewhere, such as the Middle East, China, Japan, and other Asian territories. Students develop projects on contemporary themes.

26:220:501 - (3 cr)
Microeconomics 

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.

22:839:510 - (3 cr)
Numerical Analysis 

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.

Spring semester only

22:839:614 - (3 cr)
Object Oriented Programming in Finance I

The goal of this year-long sequence of courses is to give a rigorous introduction to computer programming and software engineering with special emphasis on applications to financial engineering. Our primary programming language will be C++. This programming language is fast enough to accommodate the performance demanded in financial environments. At the same time C++ is an object oriented language and, as such, is suitable for modern software design. In this course the assumption is that students have had no background in computer programming, although even people who are familiar with some programming language will hopefully benefit and learn new material. In part I in the Fall semester the course will start with basic concepts of programming, but we quickly get into topics in object oriented programming, UML diagrams, and basic patterns. We will also include introduction to basic algorithms and data structures. In part II in the Spring semester, more advanced topics will be covered, including advanced algorithms and data structures especially through introduction to STL and boost libraries, numerical algorithms and introduction to BLAS and LAPACK libraries, design of graphical user interfaces, and concurrent programming (also known as multiprogramming).

Fall semester only

22:839:615 - (3 cr)
Object Oriented Programming in Finance II 

The goal of this year-long sequence of courses is to give a rigorous introduction to computer programming and software engineering with special emphasis on applications to financial engineering. Our primary programming language will be C++. This programming language is fast enough to accommodate the performance demanded in financial environments. At the same time C++ is an object oriented language and, as such, is suitable for modern software design. In this course the assumption is that students have had no background in computer programming, although even people who are familiar with some programming language will hopefully benefit and learn new material. In part I in the Fall semester the course will start with basic concepts of programming, but we quickly get into topics in object oriented programming, UML diagrams, and basic patterns. We will also include introduction to basic algorithms and data structures. In part II in the Spring semester, more advanced topics will be covered, including advanced algorithms and data structures especially through introduction to STL and boost libraries, numerical algorithms and introduction to BLAS and LAPACK libraries, design of graphical user interfaces, and concurrent programming (also known as multiprogramming).

Spring semester only

Prerequisites: Object Oriented Programming in Finance I (22:839:614)

26:711:564 - (3 cr)
Optimization Models in Finance 

The objective of the course is to provide the students with knowledge and skill sufficient for correct formulation, analysis and solution of optimization models. Particular attention will be devoted to models applicable to various financial planning problems, including models of risk-averse optimization. Specific topics include optimality conditions for linear and nonlinear programming, duality, mean-risk optimization, optimization of coherent measures of risk, and optimization with stochastic dominance constraints. The course will also prepare the students for independent research on problems involving risk modeling and optimization.

Pre-2011 Admits: Operations Research Models (previously called Spc. Tpc: Management Science), 26:711:685, and Optimization Models in Finance (711:564), are the same course. You may take either one or the other to count toward your core (but not both).

22:390:609 - (3 cr)
Options 

The purpose of this course is to provide students with the necessary knowledge on how to use and not to use the models for derivatives. While the course will primarily focus on payoffs, usage, pricing, hedging, and institutional details of the most fundamental or vanilla versions of Options and Futures, it will also deal in some detail with more recent studies in the theory of derivative pricing. Students will acquire a robust conceptual knowledge of the fundamental issues that determine the valuation and behavior of these instruments. Though this course focuses on the intuitive economic insights of those models, some advanced math is required, including stochastic calculus. Be prepared for some necessarily non-trivial math if you take the course.

Fall semester only

22:390:608 - (3 cr)
Portfolio Management

Students taking this course should expect to learn about financial decision making from an investor's perspective. The course will focus on the fundamental principles of risk and return, diversification, and asset allocation. Students will learn about investment strategies commonly used by mutual funds and hedge funds, as well as how to evaluate a portfolio manager's performance. There are two goals for the course. First, to provide students with a framework they can apply to help break down and understand complicated investment strategies that are commonly used by investment managers. Second, to provide students with the technical skills necessary for a career in portfolio management. Both sets of skills will be developed through case studies, homework assignments, lectures, and discussions.  

Prerequisites: 223:581 or 223:521; 223:591 or 223:520; 390:587 or 390:522; and 390:603.

22:390:670 - (3 cr)
Risk Management 

This course provides an overview of financial risk management. Emphasis will be on modeling and quantitative techniques. Students will learn how risk management is carried out in today's financial firms and about current challenges in financial risk management. Topics include value at risk, expected shortfall, stress testing, market risk, credit risk, liquidity risk, and Bayesian analysis.

This course is for 2nd-year students only.

Fall semester only

Prerequisites: Fin. Institutions & Mrkts (22:390:604) and Econometrics (26:220:507) and Financial Modeling I (22:839:571) and Numerical Analysis (22:839:510) and Object Oriented Programming in Finance II (22:839:615).

Financial Institutions and Markets (22:390:604) and Risk Management (22:390:670) are substitutable core courses. If a student takes one of them as a core course, the student can take the other as an elective.

22:390:601 - (3 cr)
Risk & Insurance Management 

This course introduces you to corporate risk management. We survey the current practices corporations use in protecting their assets from random events. You will learn of the tools firms use to measure, estimate, and mitigate a variety of risk exposures, by insurance, hedging, and diversification. Covered risk exposures include interest rate risk, fx risk, credit risk, market risk, liquidity risk and operational risk. In light of current financial markets crisis, the course will focus on risk exposures associated with financial intermediation. However, much of the material presented is equally important to non-financial institutions, multinationals in particular.

26:711:563 - (3 cr)
Stochastic Calculus for Finance

The objective of the course is to provide the students with knowledge and skill sufficient for correct formulation and analysis of continuous-time stochastic models involving stochastic integrals and stochastic differential equations. Particular attention will be devoted to application of stochastic calculus methods in finance, such as models of evolution of stock prices and interest rates, pricing of options, and pricing of other contingent claims.The course will also prepare the students for independent research on problems involving stochastic calculus techniques.

Spring semester only

Prerequisites: This course requires a strong understanding of probability. Students lacking a background in probability should take Probability (26:960:575) before taking this class.

Stochastic Calculus for Finance (26:711:563) and Stochastic Processes (26:960:580) are substitutable core courses. If a student takes one of them as a core course, the student can take the other as an elective.

26:960:580 - (3 cr)
Stochastic Processes

The course covers the theory and modeling of stochastic processes. Topics include, martingales, stopping theorems, elements of large deviations theory, Renewal Theory, Markov Chains, Semi-Markov Chains, Markovian Decision Processes. In addition, the class will cover some applications to finance theory, insurance, queueing and inventory models.

Fall semester only

Prerequisites: This course requires a strong understanding of probability. Students lacking a background in probability should take Probability (26:960:575) before taking this class.

Stochastic Calculus for Finance (26:711:563) and Stochastic Processes (26:960:580) are substitutable core courses. If a student takes one of them as a core course, the student can take the other as an elective.

NJIT CS661 - (3 cr)
Systems Simulation

This course covers the use of simulation as a tool for analyzing business and engineering problems. The two primary goals of the course are to learn how to plan, build and use simulation models and to develop an understanding of when simulation is an appropriate tool for analysis. Much of the work in the course will involve learning the mathematical and software tools for building simulation models, performing experiments with them, and interpreting the results.

Spring semester only

Prerequisites: This course requires a strong understanding of probability. Students lacking a background in probability should take Probability (26:960:575) before taking this class.

Econometrics (26:220:507), Financial Time Series (26:960:685) and Systems Simulation (NJIT CS661) are substitutable core courses. If a student takes one of them as a core course, the student can take the other(s) as elective.

22:839:638 - (1-3 cr)
Internship/Research

The M.Q.F. internship program is an integral and important enhancement to class lectures, readings, and student assignments. It is designed to provide students practical experience in the quantitative finance field with the opportunity to experience classroom theory in the business environment.

The types of training may include implementation of trading strategies for equities and currencies, analysis of stocks and bonds, identification of mispriced assets, validation of pricing models for options and other derivative securities, analysis and management of risk, and forecast of financial variables.

The student will work under the supervision of an approved employer within a specific department and will be evaluated by both the employer and the M.Q.F. advisor.

 

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