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Requirements and Core Courses

Master in Finance

Requirements and Core Courses

Current Master in Finance students will find information about key requirements and core courses on this page. Information about electives can be found here.


Requirements

All Master in Finance students must take five core courses and 11 elective courses. Eligible courses are listed below. At least five of the elective courses must be at the level 500 or higher along with five from List One of the elective courses. More information on elective courses can be viewed here. Students who aim to become an AI in their second year must complete all core courses in their first year. 

Importantly, any course not on the pre-approved elective list must be pre-approved by the Director of Graduate Studies and will not be considered unless it meets the following criteria: a) having regular homework assignments b) a final exam, and c) is a full semester (not a half semester) course.

Students are not permitted to work in any capacity during their first year of the program, as it’s preferred they concentrate on their studies. With permission of the Director of Graduate Studies, students will be allowed to work on campus during their second year after they complete the five core courses of the program.

Information for students in the condensed, one-year program

Students who have been admitted to the one-year program (as stated in their admission letter) must complete a total of 10 courses over two semesters. Individual meetings between the student and the Director of Graduate Studies will determine, on the basis of courses previously completed by the student at Princeton or another institution, which of the required core and elective courses need to be taken. Additionally, one year students cannot take classes at the Princeton School of Public & International Affairs for credit unless they get permission from the Director of Graduate Studies.

Other course requirements

At most, 5 course credits per semester can be earned towards fulfilling the requirements of the program. Each semester, the list of courses taken for credit needs to be approved by the Director of Graduate Studies before the end of the second week of classes.

Second year students cannot take 300-or-less-level courses for credit. First year students can take at most one 300-level course for credit but must have permission from the Director of Graduate Studies.

MFins can take at most one SPIA course per semester, after receiving approval from the Princeton BCF Director of Graduate Studies.

Our MFin exam policy is that all students are to be on campus throughout the exam period including each prior reading period and should not arrange travel for this time. Graduate study is a full-time commitment on the students part. The specific periods taken as vacation must not conflict with the student’s academic responsibilities, coursework, research, or teaching, and should be discussed in advance with one’s director of graduate studies, adviser. Student Vacation Policy

GPA minimums

Students must maintain an overall grade average of B (GPA = 3.0) or better as well as earn a passing grade in all core and elective courses.

In case a student completes additional courses beyond the required total number, the GPA is calculated using the grades earned in the most favorable combination of courses that still fulfills the program’s core and elective requirements.

Audited or P/D/F courses cannot be used to fulfill the program’s requirements.

Extensions for students who don’t meet the requirements

Students unable to meet the graduation requirements of the program at the end of their original program length of one or two years, either because their GPA is below the required 3.0 minimum or because they have not completed the required core and elective courses, may apply for an extension by submitting a proposal to the Director of Graduate Studies who will review it and seek the approval of the Dean of Academic Affairs of the Graduate School.

The conditions governing such proposals are the following:

  • At most two additional semesters will be granted to complete the requirements
  • The student will need to re-enroll formally for each additional semester, and full tuition will be charged for each additional semester.
  • A maximum of two courses can be re-taken for the purpose of improving the student’s GPA. Students are free to select the two courses they wish to re-take.
  • A course re-taken will appear twice on the student transcript, but only the higher grade earned will be used for the purpose of computing the student’s final GPA.
  • Courses may not be re-taken until the completion of the student’s original program length.
  • A course re-taken counts only once for the purpose of satisfying the required number of core and elective courses.
  • The new plan of study needs to be approved before the official beginning of the semester to be added.
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Core Master in Finance Courses

The core courses of the Master in Finance provide students with analytical fundamentals of modern finance, both theoretical and empirical. Descriptions of these courses can be found below or at the Registrar’s Office.

Fall Semester

FIN 501/ORF 514 – Asset Pricing I: Pricing Models and Derivatives

This course provides an introduction to the modern theory of asset pricing. Topics include: no arbitrage, Arrow-Debreu prices and equivalent martingale measures, security structure and market completeness, mean-variance analysis, Beta-pricing, CAPM, and introduction to derivative pricing.

FIN 505/ORF 505 – Statistical Analysis of Financial Data

The course is divided into three parts of approximately the same lengths: Density estimation (heavy tail distributions) and dependence (correlation and copulas); Regression analysis (linear, nonlinear, nonparametric) and robust alternatives; Support Vector Machines and Machine Learning, including convolution and recurrent neural networks. The statistical analyses, the computations, and the numerical simulations will be done in the R environment for statistical computing.

Spring Semester

FIN 502 – Corporate Finance and Financial Accounting

This course 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. The course 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.

FIN503/ORF515 – Asset Pricing II, Stochastic Calculus, and Advanced Derivatives OR FIN521 – Fixed Income, Options, and Derivatives: Models and Applications

FIN503/ORF515 begins with an overview of basic probability theory and covers the elements of stochastic calculus and stochastic differential equations that are widely used in derivatives modeling, pricing and hedging. Topics include Brownian motion, martingales, and diffusions and their uses in stochastic volatility; volatility smiles; risk management; interest-rate models; and derivatives, swaps, credit risk, and real options.

FIN521 covers models of valuation for fixed income securities. Topics include: interest rate contracts: zerocoupon bonds, coupon bonds, floating rate notes, yields, forwards and futures, swaps, options, caps, swaptions; arbitrage free pricing in discrete time: Vasiek model, Ho-Lee model, BlackDerman-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.

FIN504/ORF 504 – Financial Econometrics

This course covers econometric and statistical methods as applied to finance. Topics include measurement issues in finance, predictability of asset returns and volatilities, value at risk and extremal events, linear factor pricing and portfolio problems, intertemporal models of the stochastic discount factor and generalized method of moments, vector autoregressive and maximum likelihood methods in finance, risk neutral valuation in discrete time, estimation methods of continuous time models, volatility smiles and alternatives to Black-Scholes, and nonparametric statistical methods for option pricing.