On the Numerical Solution of Mertonian Control Problems: A Survey of the Markov Chain Approximation Method for the Working Economist
Simon Ellersgaard ()
Additional contact information
Simon Ellersgaard: University of Copenhagen
Computational Economics, 2019, vol. 54, issue 3, No 14, 1179-1211
Abstract:
Abstract Analytic solutions to HJB equation in mathematical finance are relatively hard to come by, which stresses the need for numerical procedures. In this paper we provide a self-contained exposition of the finite-horizon Markov chain approximation method as championed by Kushner and Dupuis. Furthermore, we provide full details as to how well the algorithm fares when we deploy it in the context of Merton type optimisation problems. Assorted issues relating to implementation and numerical accuracy are thoroughly reviewed, including multidimensionality and the positive probability requirement, the question of boundary conditions, and the choice of parametric values.
Keywords: HJB equation; Finite difference approximation; Merton problem (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10614-018-9865-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
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:kap:compec:v:54:y:2019:i:3:d:10.1007_s10614-018-9865-y
Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2
DOI: 10.1007/s10614-018-9865-y
Access Statistics for this article
Computational Economics is currently edited by Hans Amman
More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().