Elective Courses
The descriptions below briefly outline the elective courses.
26:223:655 - (3 credits)
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.
22:390:605 - (3 credits)
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.
22:390:658 - (3 credits)
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.
16:642:624 - (3 credits)
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).
26:198:644 - (3 credits)
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.
22:010:648 - (3 credits)
Decoding of Corporate Financial Statements
We will be examining the annual reports from many different companies and see how to quickly analyze the corporation. You will learn to focus on the important information and separate hype from facts. You will be exposed to good and bad corporations, so that you will recognize quickly what they are in the future. We will try to understand the different corporate games that are commonly being played (Sunbeam, Satyam, among many others). We will also try and understand how “risky” a business is and whether a corporation can remain solvent in the future. Finally, you will be introduced to the important topic of structuring mergers and acquisitions.
26:390:668 - (3 credits)
Empirical Finance
The application of econometric techniques to the empirical study of finance and financial economics, especially the examination of weak effects with very large samples. Among the topics examined are measurement problems in event studies, the effects of anomalies in reported prices on computed returns, and how to deal with those effects. After completing this course and Advanced Econometrics, the student should be able to evaluate critically both proposed and published studies and will become adept at designing his or her own studies.
22:390:587 - (3 credits)
Financial Management
Provides a general survey of the field, including the basic principles of corporate finance, financial markets and institutions, and investment theory. Corporate finance topics covered include: the objective of financial management, valuation of assets and associated problems in the valuation of the firm, acquisition of long-trimester assets (capital budgeting), management of short-trimester assets, capital structure and financial statement analysis. Financial markets and institutions studied include money markets, stock and bond markets, derivatives and the banking system. Investment analysis topics include portfolio theory and asset pricing models.
22:390:613 - (3 credits)
Financial Statement Analysis
This course presents techniques for analyzing a firm’s current and projected financial statements for the purposes of credit analysis, security analysis, and internal financial analysis, cash flow forecasting, time series analysis, discriminant analysis, and ‘event studies’. Topics covered include: financial distress prediction, evaluation of sort-term and long-term loan requests, financial evaluation of new products and start up firms, 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.
26:960:576 - (3 credits)
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.
22:390:681 - (3 credits)
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.
22:390:606 - (3 credits)
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 credits)
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 credits)
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 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.
22:390:654 - (3 credits)
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 credits)
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.
26:711:564 - (3 credits)
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.
22:390:608 - (3 credits)
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 credits)
Risk Management
This course introduces fundamental principles and techniques of financial risk management. Topics include the role and function of risk management in investments; categories of financial risk: market, credit and operational risk; regulatory issues of risk management; models and measurement of risk; tools and techniques of risk management: P&L models, value-at-risk, expected shortfall, extreme value theory, regression techniques, Monte-Carlo simulation, and Dempster-Shafer model; stress testing and maximum loss theory; and model risk: model validation in practice, term structure models and volatility models.
22:390:601 - (3 credits)
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.
26:960:580 - (3 credits)
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.
NJIT CS661 - (3 credits)
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.
22:839:638 - (1-3 credits)
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.
