Ph.D. and MSQ in Quantitative Finance

The Ph.D. Program in Finance at GSEFM is designed to ensure that students acquire a thorough knowledge of the theory of finance, of econometric and computational methods, as well as the structure of modern financial markets, before beginning their own research under faculty supervision.

In the first year of the program, students attend core courses in financial economics, econometrics, and mathematical methods. Furthermore, students attend courses in microeconomic or macroeconomic theory. At the end of the first year of studies, students must pass qualifying examinations in finance, econometrics, and microeconomics or macroeconomics. In the second year of the program students complete field courses in two to three fields of their choosing and begin to work on their own research. All students are required to have a faculty advisor by the end of their second year in the program. The role of the faculty advisor is to help the student to make the transition from coursework to research and to identify suitable dissertation topics. By the end of their third year in the program students will need to have completed their first research paper. The dissertation is completed in the fourth year of the program. The dissertation must be a major piece of research, and its chapters must have the potential for publication in an international scientific journal.

First-year students in the MSQ Program in Quantitative Finance enroll in the same set of courses as the first-year Ph.D. Program in Finance students. If completing their first year of studies with strong success, the MSQ Program in Quantitative Finance students are then eligible and strongly encouraged to join the Ph.D. Program in Finance from their second year of studies onwards. The MSQ Program in Quantitative Finance is completed with a Master thesis written in the final months of the second year of studies.

Ph.D. Program Structure

Pre-Semester: Mathematics, Statistics and Econometrics

First Semester: Advanced Econometrics 1 (8 CP), Advanced Financial Economics 1 (8CP), Advanced Macroeconomics 1 (8 CP) or Advanced Microeconomics 1 (8 CP), Mathematical Methods (8 CP)

Second Semester: Advanced Econometrics 2 (8 CP), Advanced Financial Economics 2 (8 CP), Advanced Macroeconomics 2 (8 CP) or Advanced Microeconomics 2 (8 CP), Programming Languages (4 CP)

Qualifying Examinations

First Semester: Field Courses, Workshop Attendance

Second Semester: Field Courses, Seminar, Workshop Attendance 

Fields Offered:

Development and International Economics (including Cross-Country Studies, Development Microeconomics, Economic Growth, International Trade)

Econometrics (including Bayesian Econometrics, Dynamic Panel Models, Econometrics of Duration and Transition Data, Long Memory in Time-Series, Non-Parametric Econometrics)

Finance (including Asset Pricing, Corporate Finance Theory, Empirical Banking, Household Finance, Option Pricing, Taxes and Finance)

Macroeconomics (including Consumption and Saving, Economic Growth, Family Macroeconomics, Household Finance, Monetary Theory and Policy, Monetary and Fiscal Policy, Numerical Methods in Macroeconomics)

Marketing (including Bayesian Modelling for Marketing, Customer Management and Social Media, Pricing and Online-Advertising, Structural Models and Competition)

Microeconomics and Management (including Behavioral Auction Theory, Behavioral Economics, Decision Making under Risk and Ambiguity, Economics of Taxation, Empirical Labor Economics, Empirics of Contracts, Experimental Economics, General Equilibrium Theory: History, Incentives in Organizations, Intergenerational Economics, Modeling Group Behavior Using Game Theory, Taxes and Finance)

Historical and Normative Foundations of Economics (including History of Economic Thought, Normative Foundations)

Workshop Attendance
Independent Studies Course (Teaching Skills)
Third-Year Research Paper
Workshop Attendance
Job Market Course
Thesis Defense

During either the third or fourth year in the program, students may spend one or two semesters abroad for a research stay at an internationally top ranked Ph.D. program. Such stays are facilitated by the faculty advisor.

First Year Courses

The details of the course offerings will differ somewhat from year to year, depending on the faculty member teaching the course in question. The following list summarizes typical first-year course contents. For more details on these courses in any given year as well as the field courses, it is best to consult the course syllabi typically retrievable on individual faculty members’ websites.

Mathematics and Statistics: real analysis, multivariable calculus, linear algebra, linear difference equation systems, introduction to MATLAB, static optimization, statistics, introduction to STATA, linear regression with STATA.
Advanced Econometrics 1: fundamentals of linear regression (OLS, SUR, 2SLS, 3SLS, GMM, QML), cross-section regression models with limited dependent variables, static panel data models.
Advanced Financial Economics 1: corporate finance, credit constraints, moral hazard, adverse selection, asymmetric information, Diamond/Dybvig model, market for corporate control
Mathematical Methods: probability theory, measure theory, stochastic processes, topology, difference and differential equations, dynamic optimization, numerical methods
Advanced Macroeconomics 1: dynamic optimization in models with representative and with heterogeneous agents, consumption, investment, saving and financial markets.  or
Advanced Microeconomics 1: theory of the household, theory of the firm, decisions under uncertainty, market equilibrium, static and dynamic games under alternative information structures.
Advanced Econometrics 2: integration and cointegration, single and multiple equation time-series models (ARMA, ARDL, VAR, VECM), spectral analysis, conditional heteroskedasticity.
Advanced Financial Economics 2: basic equilibrium asset pricing, models with heterogeneous agents or non-standard preferences, introduction to stochastic calculus and continuous-time modeling, option pricing, asset allocation, equilibrium asset pricing in continuous time, asset pricing in production economy models.
Programming Languages: major methods of programming (such as Python, R, and C) applied to research, specifically data analysis, in economics and business.
Advanced Macroeconomics 2: structure of DSGE models, monopolistic competition and pricing, strategic complementarities, optimal monetary and fiscal policy, learning. or
Advanced Microeconomics 2: contract theory (moral hazard, adverse selection, mechanism design, incomplete contracts), general equilibrium theory, welfare economics, externalities.