Bendheim Center for Finance

Director

Yacine Aït-Sahalia

Director of Graduate Studies

René A. Carmona

Executive Committee

Dilip J. Abreu, Economics

Yacine Ait-Sahalia, Economics

Alan S. Blinder, Economics

Markus K. Brunnermeier, Economics

René A. Carmona, Operations Research and Financial Engineering

Patrick Cheridito, Operations Research and Financial Engineering

Erhan Çinlar, Operations Research and Financial Engineering

Alexandre W. d’Aspremont, Operations Research and Financial Engineering

Savas Dayanik, Operations Research and Financial Engineering

Jianqing Fan, Operations Research and Financial Engineering

Harrison Hong, Economics

Harold James, History

Daniel Kahneman, Psychology, Woodrow Wilson School

Paul R. Krugman, Economics, Woodrow Wilson School

Burton G. Malkiel, Economics

Stephen Morris, Economics

John M. Mulvey, Operations Research and Financial Engineering

Jonathan A. Parker, Economics, Woodrow Wilson School

Hélène Rey, Economics, Woodrow Wilson School

José A. Scheinkman, Economics

Hyun Shin, Economics

Christopher A. Sims, Economics

K. Ronnie Sircar, Operations Research and Financial Engineering

Kenneth Steiglitz, Computer Science

Lars E. O. Svensson, Economics

Robert J. Vanderbei, Operations Research and Financial Engineering

Erik H. VanMarcke, Civil and Environmental Engineering

Mark W. Watson, Economics, Woodrow Wilson School

Wei Xiong, Economics

 

The interdisciplinary Bendheim Center for Finance offers a Master in Finance (M.Fin.) degree. The distinctive feature of Princeton’s M.Fin. program is its strong emphasis on financial economics in addition to financial engineering and computational methods. Graduates of this program will have a solid understanding of the fundamental quantitative tools from computer science, economic theory, optimization, probability, and statistics, all of which are becoming increasingly vital in the financial industry. To a greater degree than at any time in the past, there now exists a body of knowledge that is widely agreed to be essential for the proper analysis and management of financial securities, portfolios, and the financial decisions of the firms. A driving force behind these developments is a lively exchange of ideas between academia and the financial industry, a collaboration that is the closest parallel in the social sciences to the academic-private sector interactions routinely seen in engineering and the applied sciences.

The M.Fin. program is intended to prepare students for a wide range of careers both inside and outside the financial industry, including applied research, financial engineering and risk management, macroeconomic and financial forecasting, quantitative asset management, and quantitative trading. The program does not require prior work experience, although it can be a plus. The Bendheim Center provides extensive career assistance to students, including help with internships and job placement. The program has a small number of merit-based fellowships (in the form of a fraction of the full-year’s tuition cost) which are granted to top applicants.

The curriculum is designed to be completed in four terms. Admission letters will specify the expected program length. Individual meetings between students admitted to the program and the director of graduate studies will determine, on the basis of courses previously completed at Princeton or another institution, which courses need to be taken. This flexible format allows exceptionally well-prepared students to complete the program in as little as one academic year. The program is designed to be taken on a full-time basis. Classes are taught during the day, and full-time students take four or five courses per term. Given the logistics, the only possibility for part-time enrollment would be for students who already work in the Princeton area and who would be able to attend class during the day. Part-time students are expected to take a minimum of two classes per term, and a maximum of four years (eight terms) to finish the program. All students are subject to an annual review of academic progress.

Princeton’s master’s program draws upon the combined strength of a variety of departments, including the Departments of Computer Science, Economics, Operations Research and Financial Engineering, and others. The program has two major course components and a required summer internship between years one and two. First, required core courses will provide (1) the prerequisite skills in economics, finance, mathematics, and probability and statistics necessary for the study of finance at a sophisticated level; and (2) an integrated introduction to modern financial analysis. Second, a wide range of elective courses, drawn from many departments, will allow students to tailor the program to fit their own needs and interests. These courses will permit a range of opportunities for specialization and in-depth study along a number of coherent tracks of topics of interest to the student. Finally, the required summer internship is meant to provide additional practical experience in addressing real-world finance issues.

Admission Requirements

The master’s program is designed both for students with mathematical (or physics and engineering) training, who want to make finance their main field of application, and for students with an economics (or business or social science) background, who want to acquire the quantitative skills essential for well-rounded training in finance. In either case, students must have an interest in, and be able to handle, the combination of economic analysis, mathematics, econometrics, and computer science that are pervasive in modern finance. If appropriate for the student, an intensive two-week review course covering probability and topics in mathematics, as required for the core courses, is offered prior to the beginning of classes in the fall. In addition, the center organizes in September for every incoming class a four-day “boot camp” with industry professionals, where various career issues are reviewed and help is provided (including résumé writing, one-on-one videotaped interview sessions, etc.

Applicants must take either the Graduate Record Examination (GRE) or the Graduate Management Admission Test (GMAT). Non-native speakers of English who have not earned their undergraduate degree at a U.S. college or university must take either the TOEFL (Test of English as a Foreign Language) or the IELTS (International English Language Testing System).

Program Requirements

The program requirements consist of six core and ten elective courses (see the list below), with the following provisions: (1) at least five of the elective courses must be at the 500 level or above; (2) at least five of the elective courses must be taken from List 1 below.

Students must maintain an overall grade average of B or better, as well as earn a passing grade in all core and elective courses. Audited courses cannot be used to fulfill the program’s requirements.

While no master’s thesis is required, students interested in independent research may work with a Bendheim Center-affiliated faculty member on a topic relevant to finance, and by enrolling in the appropriate courses (FIN 560, 561), they can receive academic credit equivalent to one or two elective courses (thereby reducing the number of required electives).

All M.Fin. candidates are required to complete a summer internship by working at a financial institution or completing a summer research project under the direction of a Bendheim-affiliated faculty member. Students in the two-year degree program must complete this required internship during the summer between their first and second years. Students in the one-year program whose records demonstrate substantial prior professional work experience in the finance industry may be exempted from this requirement after review by program faculty. All other one-year students must complete the internship requirement the summer before they begin formal coursework in the Fall term. For these students, the M.Fin. program will formally begin July 1.

Core Courses

The core courses of M.Fin. provide students with analytical fundamentals of modern finance, both theoretical and empirical. The organization of the core courses for students entering the program is:

Asset Pricing

FIN 501, fall

ORF 515, spring

Financial Economics

ECO 362, fall

FIN 502, spring

Statistics and Econometrics

ORF 505, fall

ORF 504, spring

Elective Courses

In addition to core courses, which provide a broad survey of topics and techniques of modern finance, the program offers students the opportunity to choose from among a variety of elective courses. Some of these courses have prerequisites, or require permission of the respective instructors.

List 1: Finance Applications Courses

FIN 512 Trading and Securities Markets

FIN 515 Portfolio Theory and Asset Management

FIN 516 Topics in Corporate Finance, Corporate Governance, and Banking

FIN 518 International Financial Markets

FIN 519 Corporate Restructuring, Mergers, and Acquisitions

FIN 521 Fixed Income: Models and Applications

FIN 522 Options, Futures, and Financial Derivatives

FIN 560 Master’s Project I

FIN 561 Master’s Project II

ECO 414 Introduction to Economic Dynamics

ECO 525, FIN 595 Financial Economics I

ECO 526, FIN 596 Financial Economics II

ECO 575, FIN 575 Topics in Financial Economics

ORF 335, ECO 364 Introduction to Financial Engineering

ORF 527 Stochastic Calculus and Finance

ORF 530 Financial Data Mining

ORF 531 Computational Finance in C++

ORF 534 Financial Engineering

ORF 535 Financial Risk Management

ORF 555 Fixed Income Models

ORF 569, 570 Special Topics in Statistics and Operations Research

ORF 574 Special Topics in Investment Science

WWS 451 Special Topics in Public Affairs: Regulation of International Financial Markets

List 2: General Methodology for Finance

APC 350 Introduction to Differential Equations

APC 503 Analytical Techniques in Differential Equations

APC 518, ORF 518 Applied Stochastic Analysis and Methods

CEE 513 Introduction to Finite-Element Methods

CEE 532 Advanced Finite-Element Methods

CEE 548 Risk Assessment and Management

CHE 508 Numerical Methods for Engineers

CHE 530 Systems Engineering

COS 318 Operating Systems

COS 323 Computing for the Physical and Social Sciences

COS 333 Advanced Programming Techniques

COS 423 Theory of Algorithms

COS 425 Database and Information Management Systems

COS 432 Information Security

COS 436 Human-Computer Interface Technology

COS 444, ECO 444 Internet Auctions: Theory and Practice

COS 461 Computer Networks

ECO 418 Strategy and Information

ECO 501 Microeconomic Theory I

ECO 502 Microeconomic Theory II

ECO 503 Macroeconomic Theory I

ECO 504 Macroeconomic Theory II

ECO 512 Advanced Economic Theory II

ECO 513 Advanced Econometrics: Time Series Models

ECO 517 Econometric Theory I

ECO 518 Econometric Theory II

ECO 519 Advanced Econometrics: Nonlinear Models

ECO 521 Advanced Macroeconomic Theory I

ECO 522 Advanced Macroeconomic Theory II

ECO 523 Public Finance I

ECO 524 Public Finance II

ECO 531 Economics of Labor

ECO 541 Industrial Organization and Public Policy

ECO 551 International Trade I

ECO 552 International Trade II

ECO 553 International Monetary Theory and Policy I

ECO 554 International Monetary Theory and Policy II

ELE 491 High-Tech Entrepreneurship

FIN 567 Institutional Finance

MAE 306, MAT 302 Mathematics in Engineering II

MAE 503 Basic Numerical Methods for Ordinary and Partial Differential Equations

MAT 301, MAE 305 Mathematics in Engineering I

MAT 304 Introduction to Partial Differential Equations

MAT 305 Mathematical Programming

MAT 533, 534 Elliptic and Parabolic Differential Equations

MAT 591, 592 Applied Partial Differential Equations

MAT 593, APC 583 Wavelets: Applications of Wavelets in Mathematics and Other Fields

ORF 307 Optimization

ORF 311 Optimization Under Uncertainty

ORF 401 Electronic Commerce

ORF 474 Special Topics in Operations Research and Financial Engineering

ORF 522 Linear Optimization

ORF 523 Nonlinear Optimization

ORF 524 Statistical Theory and Methods

ORF 526 Stochastic Modeling

ORF 542 Controlled Markov Processes

ORF 547 Dynamic Programming

ORF 548 Large-Scale Optimization

ORF 549 Stochastic Programming

ORF 551 Probability Theory

ORF 553 Stochastic Differential Equations

ORF 554 Markov Processes

Tracks

Elective courses can be chosen according to either individual needs and preferences or to conform to one of the suggested tracks listed below. It is not necessary for a student to designate or complete a particular track to satisfy the master’s requirements; the tracks listed below are merely illustrations of coherent courses of study that students might choose.

Beyond the tracks listed, we offer a number of electives in corporate finance, dealing with the choice and financing of investment projects, firms’ determination of dividend policy, optimal capital structure, financial reorganization, mergers and acquisitions, start-up financing, deal structure, incentive design, valuation of high-risk projects, initial public offerings, etc. However, we believe that our students’ comparative advantage lies in other areas encompassed within the modern investment bank, such as asset management, risk management, derivatives pricing and trading, fixed-income analytics, and other areas where a quantitative background in theoretical and practical aspects of modern finance is essential.

Financial Engineering and Risk Management Track

Financial engineers design and evaluate products that help organizations manage risk return trade-offs. Financial engineering is no longer limited to quantitative traders and derivatives specialists, but is now used widely throughout the private sector for purposes including hedging foreign currency exposures, financing real investment, and managing real and financial risks. The aim of this track is to provide students with the background they need to be leaders and innovators in this growing field. The track includes courses in dynamic programming and stochastic control, financial economics, optimization under uncertainty, probability, stochastic calculus, and computational finance. Special attention is given to the development of the efficient computational techniques that are needed in “real-time” computing environments. In addition, students can elect to focus on the computer-based technologies that are becoming increasingly important in finance, such as the design of algorithms, efficient trading systems, interfaces, large databases, and the security of computer networks. Several courses provide students with the opportunity to acquire practical experience. In particular, full-time students will have the opportunity to work in a small group on actual financial engineering problems under the joint guidance of a faculty member and a high-level industry practitioner.

Quantitative Asset Management and Macroeconomic Forecasting Track

Highly trained financial specialists are increasingly utilized in the fields of portfolio management and macroeconomic forecasting. Among the quantitative tools used in this area are analysis of earnings revisions, “attribute” screening, and quantitative forecasting methods. Quantitative techniques are widely employed to control portfolio risk and to establish portfolios balanced with different assets (stocks, bonds, real estate, etc.) so as to minimize the variance of returns. Finally, major asset managers, commercial banks, life insurance companies, securities firms, etc., all employ financial economists to formulate strategies consistent with the expected performance of the macroeconomy; required skills include expertise in applied time-series analysis and an understanding of the major statistical macroeconomic models.

Financial Technologies Track

Computer-based technologies are becoming increasingly important in finance, such as algorithms, efficient trading systems, large databases, multimedia and web interfaces, parallel processing, and the security of computer networks. The continued development of e-commerce, the growth of computer-based trading, and the renewed emphasis on risk management in all firms are creating a new competitive environment where increasing the speed and lowering the costs of trading and other financial operations become essential components of success. This track gives students access to the latest tools and techniques of computer science and computational methods applied to finance.

Seminars and Computing Environment

Students will be involved in regular seminars offered by academic researchers and industry representatives and will have the opportunity to participate in collaborative projects in some of the elective courses. The Financial Engineering Laboratory (equipped with financial data feeds, personal computers, and workstations) has been set up to facilitate such projects. The program will provide a standardized computing environment based on Mathematica, Matlab, S-Plus, and Microsoft Office. Computational skills will be taught in a series of workshops and in a course on computational finance in C++.

Core Courses

ECO 362 Financial Investments

Burton G. Malkiel

Surveys the field of investments, with special emphasis on the valuation of financial assets. Issues studied include how portfolios of assets should be formed, how to measure and control risk, how to evaluate investment performance, and how to test alternative investment strategies and asset pricing models. Prerequisites: ECO 202 or the equivalent, 310, and MAT 200. Two lectures, one preceptorial.

FIN 501 Asset Pricing I: Pricing Models and Derivatives (also ORF 514)

Markus K. Brunnermeier

An introduction to the modern theory of asset pricing. Topics include no arbitrage, Arrow-Debreu prices, and equivalent martingale measure; security structure and market completeness; mean-variance analysis, beta-pricing, and CAPM; and an introduction to derivative pricing.

FIN 502 Corporate Finance and Financial Accounting

Robert L. Kimmel

Covers the basics of financial statements, the analysis and recording of transactions, and the underlying concepts and procedures. In addition, a more detailed study of some aspects of financial accounting that have widespread significance is undertaken, such as inventories, long-term productive assets, bonds and other liabilities, stockholders equity, and the statement of changes in financial position. Provides students with the skills necessary to become informed users of financial statements. Problem sets emphasize an ability to interpret and analyze financial statement disclosures. Prerequisites: none.

FIN 503 Asset Pricing II: Stochastic Calculus and Advanced Derivatives (see ORF 515)

FIN 504 Financial Econometrics (see ORF 504)

FIN 505 Modern Regression and Applied Time Series (see ORF 505)

Selected Courses

FIN 512 Trading and Securities Markets

Staff

The organization and regulation of stock markets; price formation, volatility, and liquidity in the secondary market (market microstructure). Also focuses on stock market crashes, Keynes beauty contest comparison, and herding behavior. The listing decision and the primary market for raising equity capital for firms.

FIN 515 Portfolio Theory and Asset Management

Staff

Covers a number of advanced topics related to asset management and asset pricing. Topics include mean-variance analysis, CAPM, APT, market efficiency, delegated money management, stock return predictability, bubbles and crashes, social interaction and investor behavior, security analysts and investor relations, and mutual fund performance and organization.

FIN 516 Topics in Corporate Finance, Corporate Governance, and Banking

Staff

Agency and control issues in corporate finance such as managerial compensation, the role of corporate boards, takeovers, leveraged buyouts, and bankruptcy. Also studies the role of banks and other intermediaries’ activities in facilitating investment and promoting sound corporate governance.

FIN 518 International Financial Markets

Staff

Studies the assets and institutions of international financial markets. A key difference between these markets and others is the role of exchange rates relating the value of two or more national currencies. Studies the market-making institutions, the market conventions, and market practices. Also studies the interrelationships between different assets and their pricing, trading, and use by corporations.

FIN 519 Corporate Restructuring, Mergers and Acquisitions

O. Griffith Sexton

Examines some of the most popular restructuring options available to corporate managers and constructs a framework to evaluate the implications they may have for shareholder value.

FIN 521 Fixed Income: Models and Applications

Robert Kimmel

Models of valuation for fixed-income securities. Topics include interest-rate contracts: zero-coupon bonds, coupon bonds, floating-rate notes, yields, forwards and futures, swaps, options, caps, and swaptions; arbitrage-free pricing in discrete time: Vasiek model, Ho-Lee model, and Black-Derman-Toy model; introduction to continuous-time fixed-income modeling: Black model, Heath-Jarrow-Morton; applications of arbitrage-free models to pricing of interest-rate contracts; credit risk; and mortgage-backed securities. Prerequisites: MAT 201, 202 (MAT 203, 204 recommended).

FIN 522 Options, Futures, and Financial Derivatives

Wei Xiong

The essential techniques of pricing financial derivatives, including the Black-Scholes formula, the binomial tree method, and the risk-neutral variation method. Trading strategies associated with financial derivatives for different purposes, and potential problems that can arise in the application of financial derivatives are also extensively discussed. This course is technical by nature and requires extensive use of calculus, statistics, and Excel spreadsheet programming.

FIN 531 Computational Finance in C++ (see ORF 531)

FIN 534 Financial Engineering (see ORF 534)

FIN 535 Financial Risk Management (see ORF 535)

FIN 555 Fixed-Income Models (see ORF 555)

FIN 560, 561 Master’s Project I and II

Staff

Under the direction of a Bendheim-affiliated faculty member, students carry out a master’s project and write a report.

FIN 567 Institutional Finance

Staff

Course studies financial institutions and focuses on the stability of the financial system. It covers important theoretical concepts and recent developments in financial intermediation, asset pricing under asymmetric information, behavioral finance, and market microstructure. Topics include market efficiency, asset price bubbles, herding, liquidity crisis, risk management, market design, and financial regulation.

FIN 575 Topics in Financial Economics (see ECO 575)

FIN 595 Financial Economics I (see ECO 525)

FIN 596 Financial Economics II (see ECO 526)