Dynamic Programming Theory

Tomas Bjork, Mariana Khapko () and Agatha Murgoci ()
Additional contact information
Mariana Khapko: University of Toronto
Agatha Murgoci: Ørsted

Chapter Chapter 11 in Time-Inconsistent Control Theory with Finance Applications, 2021, pp 111-128 from Springer

Abstract: Abstract In this chapter we review the theory of dynamic programming in continuous time. This can be done within the framework of a general controlled Markov process, but in order to keep the theory reasonably concrete we restrict ourselves to the case of a controlled stochastic differential equation (SDE) driven by a finite-dimensional Wiener process. The extension to an arbitrary controlled Markov process is rather obvious and we will comment upon it later. As the reader will see, the arguments in the continuous-time case will be almost exactly the same as for the discrete-time case.

Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Chapter: Dynamic Programming Theory (2021)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprfcp:978-3-030-81843-2_11

Ordering information: This item can be ordered from
http://www.springer.com/9783030818432

DOI: 10.1007/978-3-030-81843-2_11

Access Statistics for this chapter

More chapters in Springer Finance from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().