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22:223:520
Aggregate Economic Analysis - FT (3)
Introduces theory and empirical estimation of aggregate economic relationships, including the general price level, income, output, employment, and wages. Covers national income accounting and other economic data sources, consumption, investment, the banking system, and the supply of and demand for money, interest rates, prices, wages and employment, business fluctuations, and international economics.
Prerequisite: Managerial Economic Analysis (22:223:521 (FT)/22:223:581 (PT)). This course is a prerequisite to all finance electives. However, students may take Aggregate Economic Analysis during the same semester as their first finance elective.
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22:223:521
Managerial Economic Analysis - FT (3)
Introduces the aspects of economics that are most relevant to the operation of the individual firm or nonprofit organization. Covers theory of individual economic behavior, demand theory and demand estimation, cost and supply, price determination, production decisions, and industry structure.
Prerequisite: Proficiency requirements.
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22:223:581
Managerial Economic Analysis (3)
Introduces the aspects of economics that are most relevant to the operation of the individual firm or nonprofit organization. Covers theory of individual economic behavior, demand theory and demand estimation, cost and supply, price determination, production decisions, and industry structure.
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22:223:591
Aggregate Economic Analysis (3)
Introduces theory and empirical estimation of aggregate economic relationships, including the general price level, income, output, employment, and wages. Covers national income accounting and other economic data sources, consumption, investment, the banking system and the supply of and demand for money, interest rates, prices, wages and employment, business fluctuations, and international economics.
Prerequisite: Managerial Economic Analysis (22:223:521 (FT)/22:223:581 (PT)). This course is a prerequisite to all finance electives. However, students may take Aggregate Economic Analysis during the same semester as their first finance elective.
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22:223:607
Pharmaceutical Industry: Issues, Structure, and Dynamics (3)
This course contains weekly presentations by pharmaceutical industry professionals on topics relevant to the biopharmaceutical industry. The topics include drug approval process, FDA's relationship with the industry, pricing strategies, intellectual property and patents, genomics, licensing and partnering, market structure, mergers and acquisitions, and others. Students are evaluated based on three equally weighted papers of their choice.
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22:373:621
Legal, Regulatory, and Ethical Issues in the Pharmaceutical Industry (3)
This course will help aspiring executives in the pharmaceutical firms to develop the knowledge, skills, and ethical compass to succeed in this environment. The topics covered include research ethics, bioethics, intellectual property, health care reform, and drug marketing. This course exposes students to a diversity of perspectives from academic and industry points of view. It uses Harvard Business School cases that give students opportunities to learn by making executive-level decisions in real-world business context. Students will be expected to (1) participate actively in the case studies; (2) complete three written assignments of 5-8 pages; and (3) participate in one end-of-semester group presentation on a timely topic in drug policy.
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26:390:571
Investments (3)
Surveys the fundamental assumptions and the analytical techniques of the modern theory of finance. Topics include choices involving risk using utility theory and state preference, portfolio selection, capital market equilibrium and its implications for corporate finance and portfolio selections, and option theory.
This course is open to doctoral students of the Ph.D. in management program unless special permission is give by the program's director. Prerequisites: 26:223:552 and 26:960:577.
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26:390:572
Corporate Finance (3)
Basic knowledge of theoretical and empirical model building in the area of corporate finance.
This course is open to doctoral students of the Ph.D. in management program unless special permission given by the program's director. Prerequisite: 26:390:571.
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22:390:587
Financial Management (3)
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.
This same course is offered under another course number through the master's of financial analysis program (22:430:587). Prerequisite: Accounting for Managers (22:010:502 (FT)/22:010:577 (PT)) and Managerial Economics Analysis (22:223:581 (PT) and 22:223:521 (FT)).
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22:390:603
Investment Analysis and Management (3)
Provides an 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.
This course is also offered through the master's of financial analysis program under the course number 22:430:603. Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)).
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22:390:604
Financial Institutions and Markets (3)
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.
This course is also offered through the master's of financial analysis program under the course number 22:403:604. Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)).
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22:390:605
Advanced Financial Management (3)
Examines the problems faced by the corporate financial manager on the theoretical, analytical, and applied levels. The impact of the financing decision upon the value of the firm is analyzed. Theoretical and analytical aspects of the capital budgeting decision are examined in detail with emphasis on methods of incorporating risk into 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: Aggregate Economic Analysis (22:223:520 (FT)/ 2:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)).
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22:390:606
International Financial Markets (3)
Offers an understanding of the international financial structure and studies its impact on business and individuals in various nations. The course is divided into three parts: 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.
Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)).
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22:390:608
Portfolio Management (3)
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.
The master's of financial analysis program offers the identical course under course number 22:430:608. Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)).
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22:390:609
Options/Derivatives (3)
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 nontrivial math if you take the course.
The master's of financial analysis program offers the identical course under course number 22:430:609. Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)).
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22:390:611
Analysis of Fixed-Income Securities (3)
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.
The master's of financial analysis program offers the identical course under course number 22:430:611. Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)).
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22:390:612
Entrepreneurial Finance (3)
The financing problems that face a new and/or small business can be broken into financial planning, valuing, and raising capital. While these topics were discussed in other courses, they form the main portion of this course, which is designed for those planning to start a business or take over an existing business. It will also be beneficial for those planning careers that must interact with small or new business (e.g., banking, insurance, etc.).
Prerequisite: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)), Accounting for Managers (22:010:502 (FT)/22:010:577 (PT)).
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22:390:613
Financial Statement Analysis (3)
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: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)), Accounting for Managers (22:010:502 (FT)/22:010:577 (PT)).
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22:390:622
U.S. Health Care System and Pharmaceutical Managed Markets (3)
The health care industry in the United States is one of the most controversial and changing systems in the global economy. In recent years it has transformed into a conglomerate of public and private entities; each with its own agenda, funding sources, and place in the market. Topics of discussion will include characteristics of the health care system, public/private sector roles, health care markets, managed care impact, congressional proposals, health policy changes, health care reform strategies, and the role of patients/consumers. The primary focus of this course will be how these influences relate to the business of pharmaceuticals.
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22:390:639
Block: Changing the Way We Do Business (3)
This course will assist business majors in becoming part of the blockchain economy by
introducing them to the blockchain and cryptocurrency space and helping them
identify business problems where blockchain could be a good solution. It is important for business professionals to understand that despite the hype, blockchain may not always be the best solution, and thus understand what it can and cannot do, what the benefits are, and what the challenges are, so they could make the best decisions for their
businesses' future growth in this new economy.
Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)).
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22:390:641-689
Special Topics Courses (3 each)
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22:390:658
Applied Portfolio Management (3)
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 one comprehensive stock report (one long recommendation and/or one short recommendation) and present the findings of their best investment idea in front of the class. Students have the option of writing two stock reports (one long, one short sale) to maximize the skill set obtained from the
course. There is an application process
to be admitted into this course and the maximum number of students allowed into the course is eight.
Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)), Accounting for Managers (22:010:502) (FT)/22:010:577 (PT)).
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22:390:659
Health Care Finance (3)
This course is designed with an emphasis on applications of analytical tools in health care organizations. Combinations of lectures and discussions on different topics important to health care finance will enable students to develop analytical skills necessary to solve a variety of financial management problems. After completing this course, students should be able to analyze investment decisions; evaluate different sources of financing projects; analyze cost of capital; understand the issues of reimbursements including physician payments, capitated payments, and fee-for-service payments; differences between for-profit and nonprofit organizations; taxable and tax-exempt bond issues and their impact on the supply of charity care by nonprofit hospitals; and the operations of physicians' practice.
Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)).
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22:390:680
Financial Modeling for Corporate and Project Finance (3)
This is an advanced, modern finance course with the objective of studying valuation
and financial modeling in Microsoft Excel and their application in equity research and investment banking. In this course students will learn how to
utilize Excel to create a fully functioning three-statement (income
statement, balance sheet, and cash flow statement) financial model with historical and projected data. The course will culminate in a discounted cash
flow (DCF) valuation. Due to the hands-on nature of this course, attendance is critical. The objective is to be at a level of proficiency where you can take the annual report of any company, input its historical financials, project future financials, and create a DCF valuation. Students will also learn to put together trading and transaction comparables and compute key ratios to
determine a company's financial condition. We will also look at how to analyze an individual project by looking at NPV, IRR, and Payback methods. The course is designed to be comprehensive
covering the topics of valuation and financial modeling, while being contemporary and practical with the content and looking at current events in
the financial world and market to address the impact of these events on firms and their intrinsic value. Class time will be used to provide students hands-on experience and the ability to create financial models, which include income
statements, balance sheets, and cash flow statements for forecasting and investment evaluation purposes very similar to Wall Street practitioners. Students can evaluate key assumptions to stress test the feasibility of their
financial models for lending or investment purposes. Not only will students gain the useful skills of harnessing the power of Excel for financial analysis and presentation purposes, they will also learn the fundamentals of
valuation, what creates and destroys intrinsic value, and understand how to apply this knowledge to pursue and advance their careers.
Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)), Accounting for Managers (22:010:502 (FT)/22:010:577 (PT)).
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22:390:681
Hedge Funds (3)
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. Students will also manage a simulated $1 million hedge fund portfolio and design and present a hedge fund investment strategy group project.
Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)).
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22:390:690
Indexing and ETFs (3)
This is an advanced, modern finance course with the objective of studying indices and Exchange Traded Funds (ETFs) and their application in investment management. The course is designed to be comprehensive in covering the investment strategies and products that make up indexes and ultimately underlie ETFs. The contemporary and practical class content is enhanced by exposure to useful
industry resources and participants. The course is divided into two major segments. The first provides a deep dive into the theories, methodologies, and
wide variety of products (covering all asset classes) that are the foundations of index-based investing. The second segment provides a thorough
examination of ETFs from an investment strategy standpoint, including their
anatomy, mechanics, application, availability, and the ecosystem of industry participants. A semester project is required that involves working on
either a current industry challenge or investment opportunity that includes portfolio design, calculation, back-testing, and marketing. The class project includes working on teams, at times directly with industry experts, to practice
the application of material learned to actual real-world situations.
Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)), Accounting for Managers (22:010:502 (FT)/22:010:577 (PT)).
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22:390:693
Advanced Corporate Financial Modeling (3)
This course will show students how to combine two companies in Microsoft Excel to create
a mergers and acquisitions model ("Merger Model") and determine whether the combination is accretive or dilutive to earnings and cash flows, as
well as run different funding scenarios (cash, debt, stock, etc.) to determine the optimal financing for the deal. We will also create a leveraged buyout model ("LBO model"), which looks at a financial sponsor or private equity firm purchasing a company and determine the return ("IRR") to the purchaser based on different funding scenarios (amount of cash funding vs. debt funding). Due to the hands-on nature of this course, attendance is critical.
Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)), Accounting for Managers (22:010:502 (FT)/22:010:577 (PT)).
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22:390:695
Real Estate Finance (3)
The central objective of this course is to provide students with the background and tools necessary to analyze property markets from the perspective of an
institutional investor. This involves acquiring and using market and property-related information to develop projections of the expected future cash flows generated by a given property and using them to construct measures of value, risk, and return. The impact of new lending and leasing platforms on property markets will also be considered. The course provides extensive training and
certification in ARGUS, a real estate industry-specific program used for entering and compiling market, property, and lease information.
Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)), Accounting for Managers (22:010:502 (FT)/22:010:577 (PT)).
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22:390:697
Entrepreneurial Finance for Fashion and Beauty Industries (3)
Entrepreneurial Finance for Fashion and Beauty Industries is a course designed for students who plan to get engaged in working with a high-growth venture. The course focuses on financing of new ventures that are expected to grow and in which students may take a role of an entrepreneur, an adviser, an investor, or an employee. The course is created to expose students to the basic problems that are specific to financing new and growing ventures such as design of a business plan, contracting and valuation, choice of seed and follow-up financing, and financing venture's growth. The course also offers a basic coverage of venture capital and angel investors as well as a number of guest lectures from the fashion industry.
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22:390:699
Advance Topics: Finance Fashion (3)
The fashion industry has changed considerably in recent years. Terms like "fast fashion" have changed the climate, and investment in social media and international manufacturing has risen sharply. More importantly however, young or emerging designers and "creatives" gain an edge
by not remaining in an isolated bubble. To become key members of multidisciplinary teams, familiarity with core financial concepts is essential
in order to achieve a common level of understanding and communication in relation to the team's shared objectives and the firm's overall corporate drivers. The course serves to strengthen the student's grasp of financial management, investments, capital markets, and international finance and to strengthen competence in financial decision-making. This is an intermediate/advanced finance course contextualized to fashion and luxury
industries. We study how to implement advanced knowledge in various areas of finance to problems specific to fashion companies, startups, and conglomerates. We explore advanced techniques in the areas of investments, corporate finance,
financial markets and instruments, hedging, and international finance. This course is not a survey course; rather it covers in-depth intermediate to advanced topics.
This course is open only to students of the master's of business in fashion program.
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22:430:658
Research Methods for Asset Management (3)
To give students an in-depth understanding of the quantitative methods used in academia and industry. You will learn the typical methods used by a
quantitative researcher. Topics covered are probability distributions and
descriptive statistics, sampling and estimation, hypothesis testing, correlation and regression analysis, time-series analysis, principal components analysis, Monte Carlo simulation. Exercises will be performed using SAS or
Python.
This course is only available to master's of financial analysis students or M.B.A. students who receive special
permission from the director of the master's of financial analysis program.
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22:430:685
Real Estate Finance and Alt Investments (3)
This course is designed to introduce the student to the fundamentals of real estate investment analysis and the equity and debt markets that affect real estate decision-making. Emphasizing the commercial real estate sector, the student will develop
the essential skills needed to make proper qualitative decisions, understand financial terms and conditions, evaluate different underwriting structures, and investigate the relationship between owners and lenders. Students will view real estate through the prism of the corporate/institutional owner as well as the sole entrepreneur. Topics that will be discussed include legal documentation, valuation, types of mortgage loans, cash flow and income capitalization, alternative investments, commercial and residential
underwriting, lease analysis, and negotiations.
This course is only available to master's of financial analysis students or M.B.A. students who receive special permission from the director of the master's of financial analysis program.
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22:839:510
Numerical Analysis (3)
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.
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22:839:571
Financial Modeling I (3)
This is a quantitatively oriented financial economics course for the master of quantitative finance (M.Q.F.) 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.
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22:839:614
Object-Oriented Programming in Finance I (3)
The goal of this yearlong 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.
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22:839:615
Object-Oriented Programming in Finance II (3)
The goal of this yearlong 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.
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22:839:635
Blockchain and Cryptocurrency (3)
Assuming the students have no prior knowledge in the cryptocurrency and blockchain space, it is important to introduce basic concepts and an overview of the blockchain landscape. Furthermore, the course will explain blockchain and crypto market microstructure concepts and then introduce students to different data sources of both blockchain data and crypto market data. As a blockchain data scientist or a cryptocurrency analyst you would need to analyze data and understand the present and future value and risk of the blockchain project and/or the cryptocurrency, similar to analyzing any company or financial instrument.
Prerequisites: Knowledge of Python. The course is available only to students enrolled in the master's of quantitative finance program unless given special permission by the director of the program.
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22:839:636
Machine Learning in Finance and Economics (3)
The course has three parts. The first part introduces fundamentals and traditional machine-learning techniques including cross validation, regularization, regression trees, ensemble methods,
random forests, and gradient boosting. Python libraries scikit-learn ("sklearn") and XGBoost will be used. The second part will provide an
introduction to deep learning. Instead of treating deep neural networks as just another powerful algorithm, we will emphasize what they make possible in financial applications that are difficult or impossible to achieve with earlier
methods. Keras and Tensorflow will be used. Cloud computing will also be introduced to facilitate data management and training of these models. The
third part of the course is more experiential. Small student teams will work on projects to apply the techniques covered in the course. Projects will use real data and attempt to solve real problems faced in financial industry. The students will have flexibility to choose their topic based on their interest. Applications may focus on asset return predictions, credit risk, mergers, and real estate
values, among others.
Prerequisites: 22:390:603 or 22:839:603 Investment Analysis AND ability to write nontrivial code in Matlab and Python. The course is available only to students enrolled in the master's of quantitative finance program unless given special permission by the director of the program.
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22:839:637
Financial Forecasting and Simulation (3)
Forecasts of financial variables play a
prominent role in financial and business decision-making. This course provides an overview of modern statistical and econometric methods for predicting
financial variables and evaluating forecasts. Students will develop an understanding of the basic components of a forecasting model, how to build
their own forecasting models, and how to evaluate the performance of forecasting models. We emphasize intuitive understanding of the basic concepts
and techniques and practical applications to real-world data. Topics covered include linear projections; modeling and forecasting trend, seasonality, and cycles; AR, MA, ARMA, ARIMA, and VAR models; forecasting with fundamentals;
conditional forecasting models and scenarios analysis (stress testing); evaluating and combining forecasts; unit roots, cointegration, and stochastic trends; smoothing and shrinkage; ARCH, GARCH, and volatility forecast; unobserved components models and Kalman filter forecasting; data snooping, bootstrap, and reality check.
Prerequisites: Ability to write nontrivial code in Matlab and Python. Basic calculus, linear algebra, probability and statistics, and econometrics. The course is available only to students enrolled in the master's of quantitative finance program unless given special permission by the director of the program.
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22:839:662
Financial Modeling II (3)
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); multifactor 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; Ingersol: 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).
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22:839:686
Quantitative Equity Trading Strategies (3)
This course provides a comprehensive insight into quantitative trading strategies and covers most
aspects of the development life cycle of a trading strategy. This includes idea conception, using data for research and alpha generation, appropriate
modelling, back-testing and simulation, technology and infrastructure, regulatory compliance, risk management, and others. The course will provide an
introduction to financial markets, nature of market and its mechanics, various constituents of the markets and their role, importance of order types and execution details, microstructure, and more. It will also introduce a few quantitative trading methods, educate on pitfalls and limitations, give a preview of regulatory compliance, and provide experience-based view of what it takes to build and deploy a success trading strategy. The course will educate students on responsible capital allocation, risks involved in algorithmic trading, and appropriate performance matrices. An introduction to algorithmic investment management will also be provided.
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22:851:630
Market Analysis and Valuation in Real Estate (3)
This course explores the sources of property information and market data used in studies of real estate markets, and provides an in-depth analysis of trends, market activity, sales, lending, and leasing. The course includes analysis of both residential and commercial real estate and covers demographic analysis, regional growth, construction cycles, urban land markets, and location theory.
Exercises and applications focus on estimating and predicting property demand, supply, vacancy, and value using modeling in economics, statistical machine learning, and agent-based machine learning.
Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)), Accounting for Managers (22:010:502 (FT)/22:010:577 (PT)), and Real Estate Finance (22:390:695).
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22:851:632
Real Estate Development (3)
This course overviews real estate development of urban places, including the many
challenges of the development process such as analyzing market sectors and development opportunities, comprehending the development context of regulation, public policy and politics, raising investment capital, assembling land,
program formulation, building types, construction management, marketing, and sales. Examples of development projects will be presented, each focusing on specific aspects of the process. Students will learn how to access and harvest
online information to understand environmental and legal challenges to real estate redevelopment.
Prerequisites: Aggregate Economic Analysis (22:223:520 (FT)/22:223:591 (PT)), Financial Management (22:390:522 (FT)/22:390:587 (PT)), Accounting for Managers (22:010:502 (FT)/22:010:577 (PT)), Real Estate Finance (22:390:695), and Real Estate Law (22:851:650).
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22:851:650
Real Estate Law (3)
This course provides an overview of the legal issues that confront the real estate executive from the commencement of a real estate transaction and throughout the relationship between the parties to such transactions. In addition to many standard real property law concepts that will be covered, the course will focus on the transactional aspects of the real estate business, including acquisition,
disposition, development, investment, management, leasing, tax implications, and
negotiations. At the conclusion of the course, students will have the ability to
function with respect to these matters in many of the various aspects of
real estate business.
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26:223:554
Econometrics Cross Sectional (3)
This is a Ph.D. course in the applied econometrics of cross-section and panel data. 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 (defined as the solution to an optimization problem under various assumptions regarding the true data generating process). The 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. Instrumental variables, panel data, simultaneous equations, discrete dependent, limited dependent and duration models, dynamic panel models, and their applications are covered.
Only doctoral students are admitted to this course unless given special permission by the program director. Master of quantitative finance students may take this course under course number 22:839:554.
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26:223:655
Econometrics Time Series (3)
This course has a broad structure and covers many aspects of modeling and estimating financial/economic time series. In particular, we will be focusing on (i) linear regression models involving variables observed over time and (ii) "pure" univariate and multivariate time-series models. The objective is that participants gain a thorough understanding of the theory underlying time-series econometrics, which is the basis for any empirical time-series analysis of financial/economic market phenomena. The course places a particular emphasis on clearly identifying which econometric methods are appropriate under which scenarios. Estimation techniques covered will be Ordinary Least Squares (OLS) and Generalized Method of Moments (GMM).
Only doctoral students are admitted to this course unless given special permission by the program director.
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26:390:684
Floating Seminar (3 each)
The department offers specialized doctoral-level courses in Options, Financial
Institutions and Markets, Microstructure, and Machine Learning in Finance.
This course is open to doctoral students of the Ph.D. in management program unless special permission given by the program's director.
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Course List and Descriptions 
