Finance

Academic Year:

2021-22

Department or Program:

Finance

Address:

Bendheim Center for Finance, 20 Washington Road

Phone:

609-258-0940

Website:

Bendheim Center for Finance

Program offerings:

M.Fin.

Director of Graduate Studies

Caio de Almeida

Graduate Program Administrator

Melanie Heaney-Scott

Overview

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, data science, and computational methods, as well as emerging tools of Fin Tech. Graduates of this program will have a solid understanding of the fundamental quantitative tools from computer science, economic theory, optimization, probability, and statistics and machine learning, all of which are 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 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 technology, risk management, macroeconomic and financial forecasting, quantitative asset management and trading, financial consulting, and investment banking and corporate finance. 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) that may be granted to top applicants.

The curriculum is designed to be completed in four semesters. Admission letters will specify the expected program length. 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 semester. All students are subject to an annual review of academic progress.

Princeton’s M.Fin. 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, computer science, 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.

Students completing the program in two years will have the opportunity to obtain the Graduate Certificate from the Center for Statistical and Machine Learning (CSML). Students who earn this certificate will have it appear on the transcript at the time of graduation.

Applying

Application Deadline:

January 3, 11:59 p.m. Eastern Standard Time

Program Length:

2 years

Application Fee:

$75

Application Requirements:

Statement of Academic Purpose

Resume/Curriculum Vitae

Recommendation Letters

Transcripts

Fall Semester Grades

Required Tests

English Language Tests

GRE :

General Test required (Preferred) or GMAT

Additional Departmental Requirements:

Three letters of recommendation are required, however, one may be from a current or former employer.

M.Fin.

M.Fin. Requirements:

Courses:

The program requirements consist of five core and 11 elective courses. At least five of the elective courses must be at the 500 level or above, and five must be from list 1 (a list maintained by the director of graduate studies and available on the Bendheim Center's website).

Students must maintain an overall grade average of B or better, as well as earn a passing grade in all core and elective courses. Note: Neither audited nor P/D/F courses will 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 in the fall or FIN 561 in the spring), they can receive academic credit equivalent to one elective course (thereby reducing the number of required electives).

Teaching:

Second-year students may serve as Assistants in Instruction (A.I.s) in courses or work as tutors, if they have completed the 5 core courses. Each year the Undergraduate Certificate Program is in need of senior thesis tutoring for any majors outside of the Departments of Economics and Operations Research and Financial Engineering.Occasionally there is also a need for tutors for incoming first-year M.Fin. students. Tutors are required to spend a minimum of one hour per week with each tutee. Undergraduate Certificate tutoring is done on a group basis, with approximately five students per group.

The director of graduate studies must approve individual second-year M.Fin. students to serve as tutors or as A.I.s.

Additional Requirements:

Internship or Research Project
All M.Fin. candidates are required to complete a summer internship between their first and second years by working at a financial institution. It is mandatory for incoming students to attend the Math Refresher course which is offered two weeks before classes start in the fall.

Faculty

Director

Markus K. Brunnermeier

Executive Committee

Mark A. Aguiar, Economics
Sanjeev Arora, Computer Science
Yacine Aït-Sahalia, Economics
Alan S. Blinder, Economics
Markus K. Brunnermeier, Economics
René A. Carmona, Oper Res and Financial Eng
Natalie Cox, Economics
Jianqing Fan, Oper Res and Financial Eng
Harold James, History
Jakub Kastl, Economics
Nobuhiro Kiyotaki, Economics
Moritz F. Lenel, Economics
Ernest Liu, Economics
Ulrich K. Mueller, Economics
Arvind Narayanan, Computer Science
Jonathan E. Payne, Economics
Mykhaylo Shkolnikov, Oper Res and Financial Eng
Ronnie Sircar, Oper Res and Financial Eng
Mete Soner, Oper Res and Financial Eng
Robert J. Vanderbei, Oper Res and Financial Eng
Mark W. Watson, Schl of Public & Int'l Affairs

For a full list of faculty members and fellows please visit the department or program website.

Courses

Permanent Courses

Courses listed below are graduate-level courses that have been approved by the program’s faculty as well as the Curriculum Subcommittee of the Faculty Committee on the Graduate School as permanent course offerings. Permanent courses may be offered by the department or program on an ongoing basis, depending on curricular needs, scheduling requirements, and student interest. Not listed below are undergraduate courses and one-time-only graduate courses, which may be found for a specific term through the Registrar’s website. Also not listed are graduate-level independent reading and research courses, which may be approved by the Graduate School for individual students.

ECO 525 Asset Pricing (also

FIN 525

) Asset pricing in competitive markets where traders have homogeneous information as well as empirical tests of asset-pricing models and associated "anomalies" are also surveyed. Measures of riskiness and risk aversion; atemporal asset-pricing models; dynamic portfolio choice; option pricing; and the term structure of interest rates, corporate investment and financing decisions, and taxation are studied.

ECO 526 Corporate Finance (also

FIN 526

) Theories and empirical evidence regarding financial markets and institutions that focus on asymmetric information, transaction costs, or both; and rational expectation models of asset pricing under asymmetric information, dynamic models of market making, portfolio manager performance evaluation, principal-agent models of firm managerial structure, takeover bids, capital structure, and regulation of financial markets are studied.

ECO 527 Financial Modelling (also

FIN 527

) Advanced asset pricing and corporate finance including a selection from: models of financial crises and bubbles; interaction between finance and macroeconomics, derivative pricing in incomplete markets; tests of asset pricing models and associated anomalies; models of investor behavior; financial econometrics, including tests of asset pricing models and methods for high frequency data. Pre-requisites: ECO 525 and 526 (526 may be taken concurrently).

FIN 501 Asset Pricing I: Pricing Models and Derivatives (also

ORF 514

) Provides an introduction of the modern theory of asset pricing. Topics include: (i) no arbitrage, Arrow-Debreu prices and equivalent martingale measure; (ii) security structure and market completeness; (iii) mean-variance analysis, Beta-Pricing, CAPM; and (iv) introduction to derivative pricing.

FIN 502 Corporate Finance and Financial Accounting Modern financial theory and its implications for decisions faced by corporate financial officers. We focus on investment decisions and capital budgeting under various assumptions about the investment environment (for example, certain or uncertain outcomes) and the legal/regulatory environment (such as different types of tax regimes). We also examine financing decisions concerning the type of securities to be issued, amount of dividends to be paid, etc., plus a selection of additional topics, such as convertible/hybrid securities, real options, or corporate structure and control are also covered.

FIN 515 Portfolio Theory and Asset Management A number of advanced topics related to asset management and asset pricing are discussed, including mean-variance analysis, CAPM, APT, market efficiency, delegated money management, stock return predictability, bubble and crashes, social interaction and investor behavior, security analysts and investor relations, and mutual fund performance and organization.

FIN 516 Topics in Finance Agency and control issues in corporate finance such as managerial compensation, the role of corporate boards, takeovers, leveraged buyouts and bankruptcy. Course also studies the role of banks and other intermediaries' activities in facilitating investment and promoting sound corporate governance.

FIN 519 Corporate Restructuring, Mergers and Acquisitions Examines some of the most popular restructuring options available to corporate managers and will construct a framework to evaluate the implications they may have for shareholder value.

FIN 521 Fixed Income: Models and Applications Models of valuation for fixed income securities. Topics include: (i) interest rate contracts: zerocoupon bonds, coupon bonds, floating rate notes, yields, forwards and futures, swaps, options, caps, swaptions; (ii) arbitrage free pricing in discrete time: Vasiek model, Ho-Lee model, BlackDerman-Toy model; (iii) introduction to continuous-time fixed income modeling: Black model, Heath-Jarrow-Morton; (iv) applications of arbitrage free models to pricing of interest rate contracts; (v) credit risk; (vi) mortgage-backed securities. Prerequisites: FIN501, MAT201-202 and recommend MAT203-204. Meets concurrently with ECO 466.

FIN 522 Options, Futures and Financial Derivatives Derivative securities--assets whose value depends on the value of other more basic underlying assets--are not only an important asset in their own right, but the central intuition provided by derivative securities pricing--the no-arbitrage principle--ties together many areas in finance. This course discusses the consequences of no-arbitrage for asset pricing and corporate finance. This course meets concurrently with ECO 465.

FIN 523 Forecasting and Time Series Analysis Course develops a range of models, including macroeconomic ones, appropriate for the description and prediction of time series data. A by-product of this exposure is a greater appreciation of the assumptions implicit in regression analysis and econometrics. The primary focus is upon developing, applying, and critically evaluating statistical models that are appropriate in varying conditions. Each class of models is motivated by considering a particular well-known data series. The use of these models is facilitated through interactive, graphical computer software using a powerful graphical environment supported on department workstations.

FIN 560 Master's Project I Under the direction of a Bendheim affiliated faculty member, students carry out a master's project, write a report, and present the results in the form of a poster or an oral presentation in front of an examining committee.

FIN 561 Master's Project II Under the direction of a Bendheim affiliated faculty member, students carry out a master's project, write a report, and present the results in the form of a poster or an oral presentation in front of an examining committee.

FIN 567 Institutional Finance,Trading and Markets Financial institutions play an increasingly dominant role in modern finance. This 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 568 Behavioral Finance Traditional economics and finance typically use the simple "rational actor" model, where people perfectly maximize, and efficient financial markets. We will present models that are psychologically more realistic than this standard model. About 30% of the course will be devoted to economics, 70% to finance. Applications to economics will include decision theory, happiness, fairness, and neuroeconomics. Applications to finance will include theory and evidence on investor psychology, predictability of the stock market and other markets, limits to arbitrage, bubbles and crashes, experimental finance, and behavioral corporate finance

FIN 580 Quantitative Data Analysis in Finance The course gives a broad introduction to the techniques of machine learning, and places those techniques within the context of computational finance. Topics include parametric and non-parametric regression, and supervised learning techniques. Methods covered include linear models, logistic regression, additive models, LASSO, kernel methods, clustering methods and applications, support vector machines and classification. We also discuss the implementation of dimension reduction techniques, including principal components analysis. Examples are taken from financial models. FIN 505 is considered the prerequisite of the course.

FIN 581 Entrepreneurial Finance, Private Equity and Venture Capital This course explores how technology-based start-up ventures are founded, managed and financed. Specific emphasis is put on the early stages of development. The goal is to offer perspectives on the "two sides of the coin": the entrepreneur's perspective and the financier's perspective (in particular the venture capitalist).

FIN 591 Cases in Financial Risk Management Course examines the concept of risk and its mitigation, and how the ideas can be applied in the practice of risk management for financial and non-financial companies. The basic toolkit draws on economics, probability theory and statistics, and they are integrated with more advanced concepts drawn from portfolio choice, derivative securities and dynamic hedging. Overall aim of the course is to demonstrate how the main concepts have practical applications.

FIN 592 Asian Capital Markets Course explores the increasing weight of Asia in global equity financial markets and its implications, and frames the discussion in the macro-economic context of the globalization of financial markets and the evolution of the global monetary system. Course puts particular emphasis on concepts of economic development, market efficiency, and corporate governance. Discussions combine analysis of historical trends and recent data and events with insights from practical experience in Asian equity markets. Course also explicitly considers the policy decisions faced by the US and Chinese governments relative to existing global imbalances.

FIN 593 Financial Crises The use economic theory and empirical evidence to study the causes of financial crises and the effectiveness of policy responses to them. Particular attention given to some of the major economic and financial crises of the past century and to the crisis that began in August 2007.

FIN 594 Chinese Financial and Monetary Systems This course aims to provide an in-depth coverage of China's monetary and financial systems, with a focus on their distinct characteristics. The objective is to understand the role provided by the financial system in China's economic development, as well as the investment opportunities and risk presented by the system to the outside world.

ORF 504 Financial Econometrics (also

FIN 504

) This course covers econometric and statistical methods as applied to finance. Topics include: (i) Measurement issues in finance (ii) Predictability of asset returns and volatilities (iii) Value at Risk and extremal events (iv) Linear factor pricing and portfolio problems (v) Intertemporal models of the Stochastic Discount Factor and Generalized Method of Moments (vi) Vector Autoregressive and maximum likelihood methods in finance (vii) Risk Neutral valuation in discrete time (viii) Estimation methods for continuous time models (ix) Volatility smiles and alternatives to Black-Scholes (x) Nonparametric statistical methods for option pricing.

ORF 505 Statistical Analysis of Financial Data (also

FIN 505

) Linear and mixed effect models. Nonlinear regression. Nonparametricegression and classification. Time series analysis: stationarity and classical linear models (AR, MA, ARMA, ..). Nonlinear and nonstationary time series models. State space systems, hidden Markov models and filtering.

ORF 515 Asset Pricing II: Stochastic Calculus and Advanced Derivatives (also

FIN 503

) Course begins with an overview of basic probability theory and covers the elements of stochastic calculus and stochastic differential equations that are widely used in modern financial applications. Topics include the Poisson process, Brownian motion, martingales, diffusions and their connection with partial differential equations. Examples from applications include the Black-Scholes option pricing and hedging theory, bond pricing and stochastic volatility models.

ORF 531 Computational Finance in C++ (also

FIN 531

) Introduce the student to the technical and algorithmic aspects of a wide spectrum of computer applications currently used in the financial industry, and to prepare the student for the development of new applications. The student will be introduced to C++, the weekly homework will involve writing C++ code, and the final project will also involve programming in the same environment.

ORF 535 Financial Risk and Wealth Management (also

FIN 535

) This course is about measuring, modeling and managing financial risks. It introduces the variety of instruments that are used to this effect and the methods of designing and evaluating such instruments. Topics covered include risk diversification, planning models, market and nonmarket risks, and portfolio effects. Lectures meet concurrently with ORF 435. Credit for graduate course requires completion of additional assignments.

ORF 545 High Frequency Markets: Models and Data Analysis (also

FIN 545

) An introduction to the microstructure of modern electronic financial markets and high frequency trading strategies. Topics include market structure and optimization techniques used by various market participants, tools for analyzing limit order books at high frequency, and stochastic dynamic optimization strategies for trading with minimal market impact at high and medium frequency. The course makes essential use of high-frequency futures data, accessed using the Kdb+ database language. Graduate credit requires completion of extended and more sophisticated homework assignments.

ORF 574 Special Topics in Investment Science (also

FIN 574

) Emphasis on quantitative analysis of markets, trading strategies, risk and return profiles and portfolio analysis. Students develop portfolios of hedge funds; analyze trading models for various hedge fund styles; develop Value-at-Risk analysis of various trading systems and portfolios; analyze relationship between macro-economic variables and various hedge fund trading strategies; analyze hedge funds from the standpoint of asset allocation and efficient frontier models. We will also bring in experts and practitioners in a number of hedge fund trading strategies to add industry feel and context to the lectures and exercises.