The Annals of Applied Probability
- Ann. Appl. Probab.
- Volume 27, Number 1 (2017), 485-516.
Convex duality for stochastic singular control problems
We develop a general theory of convex duality for certain singular control problems, taking the abstract results by Kramkov and Schachermayer [Ann. Appl. Probab. 9 (1999) 904–950] for optimal expected utility from nonnegative random variables to the level of optimal expected utility from increasing, adapted controls. The main contributions are the formulation of a suitable duality framework, the identification of the problem’s dual functional as well as the full duality for the primal and dual value functions and their optimizers. The scope of our results is illustrated by an irreversible investment problem and the Hindy–Huang–Kreps utility maximization problem for incomplete financial markets.
Ann. Appl. Probab., Volume 27, Number 1 (2017), 485-516.
Received: October 2014
Revised: March 2016
First available in Project Euclid: 6 March 2017
Permanent link to this document
Digital Object Identifier
Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
Primary: 93E20: Optimal stochastic control 91G80: Financial applications of other theories (stochastic control, calculus of variations, PDE, SPDE, dynamical systems) 46N10: Applications in optimization, convex analysis, mathematical programming, economics 91B08: Individual preferences
Bank, Peter; Kauppila, Helena. Convex duality for stochastic singular control problems. Ann. Appl. Probab. 27 (2017), no. 1, 485--516. doi:10.1214/16-AAP1209. https://projecteuclid.org/euclid.aoap/1488790833