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 and monetary economics, relying on analytical and computational methods. Graduates of this program will come away with fundamental quantitative tools of economic theory, probability, statistics, optimization, computer science, and machine learning. 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 financial engineering and risk management, quantitative asset management, macroeconomic and financial forecasting, quantitative trading, and applied research.
The program does not require prior work experience, although it can be a plus. The Bendheim Center provides comprehensive career assistance to students, including personalized on-campus recruiting with our corporate partners.
Our Manager of Career Development also works with students on an individual and group basis to provide support with interview preparation, internships, and job placement.
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 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, The Center for Statistics and Machine Learning, and others. Over the last several years, the program has expanded to include new courses in machine learning, fintech, data science and entrepreneurship, to name a few.
The program has two major course components and a required summer internship between years one and two. First, there are required core courses in mathematical finance, economics, probability, statistics, and financial econometrics; all necessary for the study of finance at a sophisticated level and an integrated introduction to modern financial analysis, and second, an integrated introduction to modern financial analysis. Students can choose from a wide range of elective courses, drawn from many departments, to tailor the program to fit their own needs and interests. These courses permit a range of opportunities for specialization and in-depth study of topics of interest, along several coherent tracks. Finally, the required summer internship is meant to provide additional practical experience in addressing real-world finance issues.
Students choose from three program tracks based on their interests and goals: (1) Quantitative Asset Management - Designing and evaluating financial products that help organizations manage risk-return trade-offs; (2) Data Science & Financial Technologies - Computer-based technologies and their increasingly important use of big data in finance; (3) Valuation & Macroeconomic Analysis - Strategic understanding of firm's valuation and structural macroeconomic conditions.
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.
