PhD in Financial Engineering

Program Overview

Program Details

Degree

Doctor of Philosophy

School

School of Business

Department

School of Business Graduate Program

Available

On campus

Overview

The interdisciplinary Ph.D. program in Financial Engineering at Stevens prepares students to become thoughtful researchers who can think about creative applications of technology and quantitative methods in building innovative solutions, designing new models, predicting risk and optimizing portfolios.

Who Should Apply

The Stevens Ph.D. in Financial Engineering is suitable for full-time students who are interested in pursuing careers in academia; however, most graduates go on to top-level positions in the financial industry, where they create new models or approaches to solve complex problems.

Required Courses

Every doctoral student at Stevens completes PRV 961 Ph.D. Signature Course as part of their studies. In addition, Ph.D. students in the Financial Engineering program complete either MGT 719 Research Methods or SYS 710 Research Methodologies.

Area-Specific Courses

Working with their advisor, students choose from among the following courses to tailor their studies to their particular area of research interest. Additional courses may be substituted in with approval from the Ph.D. committee.

Quantitative Methods

• FE 641 Advanced Multivariate Statistics
• FE 646 Optimization Models and Methods in Finance
• MA 611 Probability
• MA 612 Mathematical Statistics
• MA 623 Stochastic Processes
• MA 629 Convex Analysis and Optimization
• MA 630 Numerical Models of Optimization
• MA 653 Numerical Solutions of Partial Differential Equations
• MA 655 Optimal Control Theory
• MA 661 Dynamic Programming and Stochastic Optimal Control
• MA 662 Stochastic Programming
• FE 710 Applied Stochastic Differential Equations
• FE 720 Volatility Surface: Risk and Models

Domain Tools

• FE 635 Financial Enterprise Risk Engineering
• FE 655 Systemic Risk and Financial Regulation
• FE 622 Simulation Methods in Comp. Finance and Economics
• FE 670 Algorithmic Trading Strategies
• FE 672 Modern Market Structure and HFT Strategies
• CS 541 Artificial Intelligence
• CS 559 Machine Learning: Fundamentals and Applications
• CS 590 Algorithms
• CS 600 Advanced Algorithm Design and Implementation
• BIA 658 Social Network Analytics and Visualization
• BIA 810 Cognitive Computing

Domain-Specific Research Topics

Each course in the FE 801 series offers a deep dive into a particular area of financial engineering research. Students must complete one course from the below.

• Advanced Topics in Portfolio Optimization
• Advanced Topics in Market Microstructure and Algorithmic Trading
• Advanced Topics in Financial Risk Modeling
• Advanced Topics in Systemic Risk Modeling

Dissertation

Following completion of all written exams and coursework, students are required to write and defend a dissertation in a selected area of concentration. It is expected that doctoral dissertations will make significant contributions to the creation of knowledge and the development of theory and practice in a selected area.

Admission Criteria

Admission to the Ph.D. program is decided by the Ph.D. program committee at the School of Business, and is based on a review of the candidate’s scholastic record, professional accomplishments, and the fit between the student's research objectives and those of the school’s faculty.

• A bachelor's degree from an accredited institution, preferably in math, computer science, physics, engineering or finance.
• For international students: Candidates must achieve a TOEFL score of at least 90 or an IELTS score of at least 6.5 in each component.
• Valid GMAT or GRE scores. Admission to School of Business programs is very competitive; excellent scores are required for candidates to be accepted.
• A statement of purpose describing, in three pages, the applicant’s research interests and rationale, and general career objectives.
• Current résumé or curriculum vitae.
• Official transcripts for accredited schools of higher learning attended. Typically, a GPA of 3.0 (on a 4-point scale) or better at the bachelor’s level, and 3.5 or better at the master’s level, are required.
• Three letters of recommendation.
• Evidence of prior scholarly work. This work should be written solely by the applicant; published work under sole authorship will be highly valued.