
Steven Shreve
· Orion Hoch Professor of Mathematical Sciences, Mellon College of Science, and by courtesy, Tepper School of BusinessVerifiedCarnegie Mellon University · Economics
Active 1977–2022
About
Steven Shreve is the Orion Hoch Professor of Mathematical Sciences at the Mellon College of Science and by courtesy, at the Tepper School of Business at Carnegie Mellon University. His recent research has focused on problems in financial mathematics, including models for derivative securities, utility maximization especially in the presence of transaction costs, optimal execution of large financial transactions, and the principal agent problem related to bank trader compensation. He constructs and analyzes continuous-time models using stochastic calculus in these areas. Additionally, Shreve has worked on modeling queueing systems in heavy traffic when tasks have deadlines for completion. His research involves approximating queue lengths by diffusions and measure-valued diffusions when tasks have attributes such as lead times until deadlines expire. Recently, his work has integrated these areas into the construction of diffusion approximations for limit-order books that govern trading on electronic exchanges, in collaboration with colleagues including John Lehoczky and Ph.D. advisee Christopher Almost.
Research topics
- Mathematics
- Computer Security
- Computer Science
- Statistics
- Economics
- Applied mathematics
- Mathematical analysis
- Statistical physics
- Econometrics
- Mathematical economics
- Geometry
- Business
- Quantum mechanics
- Physics
Selected publications
Lecture notes in mathematics · 2022 · 2 citations
- Mathematics
- Applied mathematics
- Statistical physics
SIAM Journal on Financial Mathematics · 2022
1st authorCorresponding- Computer Science
- Computer Security
- Computer Science
Since the financial crisis of 2008, clawback provisions have been implemented by several high-profile banks and are also required by regulators in order to mitigate the cost of financial failures and to deter excessive risk taking. We construct a model to investigate the long-term effect on the bank's revenue of deferring (escrowing) a trader's bonuses to facilitate clawback. We formulate the question by setting up an infinite-horizon dynamic programming model. Within this model, the trader's optimal investment and consumption strategy, with and without bonus escrow, can be expressed by explicit analytic formulas. These formulas enable calculation and comparison of the bank's total expected revenue under the two bonus payout schemes. The results of the comparison depend on the parameters describing the trader's risk appetite, the discount factor, and the bank's level of patience, in addition to the market parameters. In particular, when the bank's total expected discounted revenue is finite under both types of bonus payment schemes and the bank is sufficiently patient, the bank benefits by escrowing the trader's bonus, although not escrowing the trader's bonus brings better short-term revenue.
Diffusion Limit of Poisson Limit-Order Book Models
arXiv (Cornell University) · 2020
- Statistical physics
- Mathematics
- Applied mathematics
This ia a companion paper to Almost, Lehoczky, Shreve & Yu \cite{ALSY}, where the rationale for studying the diffusion limit of Poisson limit-order book models is explained and the results of a particular "representative" model are detailed. This paper contains the proofs and technical details cited in that work.
Authors group · 2019-12-06
dataset1st authorCorrespondingA free boundary problem related to singular stochastic control
Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) · 2018-06-29 · 20 citations
articleOpen access1st authorCorrespondingAbstract: "It is desired to control a multi-dimensional Brownian motion by adding a (possibly singularly) continuous process to its n[superscript th] components so as to minimize an expected infinite-horizon discounted running cost. The Hamilton-Jacobi-Bellman characterization of the value function is a variational inequality which has a unique twice continuously differentiable solution. The optimal process is constructed by solving the Skorokhod problem of reflecting the Brownian motion along a free boundary in the (0,0,..., -1) direction."
Equivalent martingale measures and optimal market completions
Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) · 2018-06-29 · 3 citations
articleOpen accessSenior authorAbstract: "Optimal fictitious completions of an incomplete financial market are shown to be associated with exponential martingales (not just local martingales) and, therefore, to 'an optimal equivalent martingale measure'. Results of independent interest, in the theory of continuous-time martingales, are derived as well."
Heavy traffic analysis for EDF queues with reneging
Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) · 2018-06-29 · 51 citations
articleOpen accessSenior authorThis paper presents a heavy-traffic analysis of the behavior of a single-server queue under an Earliest-Deadline-First (EDF) scheduling policy in which customers have deadlines and are served only until their deadlines elapse. The performance of the system is measured by the fraction of reneged work (the residual work lost due to elapsed deadlines) which is shown to be minimized by the EDF policy. The evolution of the lead time distribution of customers in queue is described by a measure-valued process. The heavy traffic limit of this (properly scaled) process is shown to be a deterministic function of the limit of the scaled workload process which, in turn, is identified to be a doubly reflected Brownian motion. This paper complements previous work by Doytchinov, Lehoczky and Shreve on the EDF discipline in which customers are served to completion even after their deadlines elapse. The fraction of reneged work in a heavily loaded system and the fraction of late work in the corresponding system without reneging are compared using explicit formulas based on the heavy traffic approximations. The formulas are validated by simulation results.
A duality method for optimal consumption and investment under short-selling prohibition
Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) · 2018-06-29 · 54 citations
articleOpen accessSenior authorAbstract: "A continuous-time, consumption/investment problem on a finite horizon is considered for an agent seeking to maximize expected utility from consumption plus expected utility from terminal wealth. The agent is prohibited from selling stocks short, so the usual martingale methods for solving this problem do not directly apply. A dual problem is posed and solved, and the solution to the dual problem provides information about the existence and nature of the solution to the original problem. When the market coefficients are constant, the value functions for both problems are provided in terms of solutions to linear, second-order, partial differential equations. If, furthermore, the utility functions are of the power form, the solutions to these equations take a particularly simple form, as do the formulas for the optimal consumption and investment processes."
Mimicking an Itô process by a solution of a stochastic differential equation
The Annals of Applied Probability · 2013-06-21 · 111 citations
articleOpen accessSenior authorGiven a multi-dimensional Itô process whose drift and diffusion terms are adapted processes, we construct a weak solution to a stochastic differential equation that matches the distribution of the Itô process at each fixed time. Moreover, we show how to match the distributions at each fixed time of functionals of the Itô process, including the running maximum and running average of one of the components of the process. A consequence of this result is that a wide variety of exotic derivative securities have the same prices when the underlying asset price is modeled by the original Itô process or the mimicking process that solves the stochastic differential equation.
Utility Maximization Trading Two Futures with Transaction Costs
SIAM Journal on Financial Mathematics · 2013-01-01 · 15 citations
articleSenior authorAn agent invests in two types of futures contracts, whose prices are possibly correlated arithmetic Brownian motions, and invests in a money market account with a constant interest rate. The agent pays a transaction cost for trading in futures proportional to the size of the trade. She also receives utility from consumption. The agent maximizes expected infinite-horizon discounted utility from consumption. We determine the first two terms in the asymptotic expansion of the value function in the transaction cost parameter around the known value function for the case of zero transaction cost. The method of solution when the futures are uncorrelated follows a method used previously to obtain the analogous result for one risky asset. However, when the futures are correlated, a new methodology must be developed. It is suspected in this case that the value function is not twice continuously differentiable, and this prevents application of the former methodology.
Recent grants
Stochastic Analysis with Applications to Finance
NSF · $651k · 2009–2016
Mathematical Finance and Stochastic Networks
NSF · $523k · 2004–2009
Frequent coauthors
- 65 shared
Ioannis Karatzas
- 63 shared
John P. Lehoczky
Carnegie Mellon University
- 36 shared
Łukasz Kruk
Maria Curie-Skłodowska University
- 18 shared
Shu-Ngai Yeung
Carnegie Mellon University
- 14 shared
Kavita Ramanan
- 8 shared
Dimitri P. Bertsekas
- 7 shared
H. Meté Soner
- 6 shared
Suresh Sethi
The University of Texas at Dallas
Education
- 1983
Ph.D., Mathematics
University of California, Berkeley
- 1979
M.S., Mathematics
University of California, Berkeley
- 1977
B.S., Mathematics
University of California, Berkeley
- Resume-aware match score
- Save to shortlist
- AI-drafted outreach
See your match with Steven Shreve
PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.
- Free to start
- No credit card
- 30-second signup