Ph.D. Operations Research and Financial Engineering
Bachelor's degree
In Princeton (USA)
Description
-
Type
Bachelor's degree
-
Location
Princeton (USA)
Foundations
The ORFE program places a strong emphasis on mathematical and computational tools. Students in ORFE develop a unique set of skills that build upon a solid foundation in probability, statistics, and optimization.
Applications
The theoretical foundations of ORFE are of central importance in many complex problems in engineering and science. Students and faculty in ORFE work in a broad range of application areas, such as finance, energy, health, risk analysis, biostatistics, genomics, machine learning, operations research, stochastic networks, signal and image processing, automated vehicle control systems, optimal design of engineered systems, robotics, astrophysics, and homeland security.
Impact
Graduates of the Ph.D. program work in academia, research organizations, and industry. Many ORFE graduates hold faculty positions at top universities.
The department offers two degree programs: the Doctor of Philosophy (Ph.D.) in Operations Research and Financial Engineering, and a Master of Science in Engineering (M.S.E.). These programs provide a great deal of flexibility for students in designing individual plans of study and research according to their needs and interests. The department is a major participant in the Master of Finance (M.Fin.) program offered through the Bendheim Center for Finance.
Facilities
Location
Start date
Start date
Reviews
Subjects
- Probability
- Computational
- Programming
- Derivatives
- Financial Training
- Trading Strategies
- IT risk
- Engineering
- Industry
- Systems
- Planning
- Project
- Financial
- Finance
- Calculus
- Statistics
- Trading
- Hedge Fund
- Risk Analysis
- Risk
Course programme
FIN 501 Asset Pricing I: Pricing Models and Derivatives (also
ORF 514
ORF 504 Financial Econometrics (also
FIN 504
ORF 505 Statistical Analysis of Financial Data (also
FIN 505
ORF 509 Directed Research I Under the direction of a faculty member, Ph.D. and M.S.E. students carry out research, write a report each, and present the results. Of these, 509 is normally taken during the first year of study. Doctoral students should complete 510 one semester prior to taking the general examination.
ORF 510 Directed Research II Under the direction of a faculty member, Ph.D. and M.S.E. students carry out research, write a report each, and present the results. Of these, 509 is normally taken during the first year of study. Doctoral students should complete 510 one semester prior to taking the general examination.
ORF 511 Extramural Summer Project Summer research project designed in conjunction with the student's advisor and an industrial, NGO, or government sponsor, that will provide practical experience relevant to the student's course of study. Start date no earlier than June 1. A research report and sponsor's evaluation are required.
ORF 515 Asset Pricing II: Stochastic Calculus and Advanced Derivatives (also
FIN 503
ORF 522 Linear and Nonlinear Optimization Theoretical concepts underlying linear programming, with computer implementations of some of the different methods. The topics covered include duality theory, the simplex method, interior point methods, related numerical issues, and modeling paradigms.
ORF 523 Convex and Conic Optimization An introduction to the central concepts needed for studying the theory, algorithms, and applications of nonlinear optimization problems. Topics covered include first- and second-order optimality conditions; unconstrained methods, including steepest descent, conjugate gradient, and quasi-Newtonian methods; constrained active-set methods; and duality theory and Lagrangian methods. Prerequisite: linear optimization.
ORF 524 Statistical Theory and Methods A graduate level introduction to statistical theory and methods. It introduces some of the most important and commonly-used principles of statistical inference and covers the statistical theory and methods for point estimation, confidence intervals, and hypothesis testing, and the applications of the fundamental theory to linear models and categorical data.
ORF 525 Statistical Learning and Nonparametric Estimation An introduction to the most important and broadly utilized statistical methods used in many scienti¿c data analysis, including general linear, mixed-e¿ects, generalized linear models, regression and ANOVA models. The methodological power of statistics will be emphasized. Objectives of this course are to give students a solid understanding of these methods, and o¿er them experience in applying these methods to real data using statistical computing packages and interpreting results. For master's/Ph.D. students and advanced undergraduates.
ORF 526 Probability Theory Graduate introduction to probability theory beginning with a review of measure and integration. Topics include random variables, expectation, characteristic functions, law of large numbers, central limit theorem, conditioning, martin- gales, Markov chains, and Poisson processes.
ORF 527 Stochastic Calculus An introduction to stochastic analysis based on Brownian motion. Topics include local martingales, the Ito integral and calculus, stochastic differential equations, the Feynman-Kac formula, representation theorems, Girsanov theory, and applications in finance.
ORF 531 Computational Finance in C++ (also
FIN 531
ORF 534 Quantitative Investment Management (also
FIN 534
ORF 535 Financial Risk Management (also
FIN 535
ORF 538 PDE Methods for Financial Mathematics An introduction to analytical and computational methods common to financial engineering problems. Aimed at PhD students and advanced masters students who have studied stochastic calculus, the course focuses on uses of partial differential equations: their appearance in pricing financial derivatives, their connection with Markov processes, their occurrence as Hamilton-Jacobi-Bellman equations in stochastic control problems, and analytical, asymptotic, and numerical techniques for their solution.
ORF 542 Stochastic Optimal Control Deterministic optimal control, dynamic programming, and Pontryagin maximum principle. Controlled diffusion processes and stochastic dynamic programming. Hamilton-Jacobi-Bellman equation, viscosity solutions. Merton problem, singular optimal control, option pricing via utility maximization.
ORF 544 Stochastic Optimization This course provides a unified presentation of stochastic optimization, cutting across classical fields including dynamic programming (including Markov decision processes), stochastic programming, (discrete time) stochastic control, model predictive control, stochastic search, and robust/risk averse optimization, as well as related fields such as reinforcement learning and approximate dynamic programming. Also covered are both offline and online learning problems. Considerable emphasis is placed on modeling and computation.
ORF 550 Topics in Probability (also
APC 550
ORF 554 Markov Processes Markov processes with general state spaces; transition semigroups, generators, resolvants; hitting times, jumps, and Levy systems; additive functionals and random time changes; killing and creation of Markovian motions.
ORF 557 Stochastic Analysis Seminar Recent developments in the theory and applications of the analysis of random processes and random fields. Applications include financial engineering, transport by stochastic flows, and statistical imaging.
ORF 558 Stochastic Analysis Seminar Recent developments in the theory and applications of the analysis of random processes and random fields. Applications include financial engineering, transport by stochastic flows, and statistical imaging.
ORF 566 High Dimensional Statistics Course is on statistical theory and methods for high-dimensional statistical learning and inferences arising from processing massive data from various scientific disciplines. Emphasis is given to penalized likelihood methods, independence screening, large covariance modeling, and large-scale hypothesis testing. The important theoretical results are proved.
ORF 569 Special Topics in Statistics and Operations Research Advanced topics in statistics and operations research or the investigation of problems of current interest.
ORF 570 Special Topics in Statistics and Operations Research (also
ELE 578
ORF 574 Special Topics in Investment Science (also
FIN 574
Ph.D. Operations Research and Financial Engineering