Dynamic programming and mean-variance hedging with partial execution risk

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

In this paper I consider a hedging problem in an illiquid market where there is a risk that the hedger's order to buy or sell the underlying asset may be executed only partially. In this setting, I find a mean-variance optimal hedging strategy by the dynamic programming method. The solution contains a new endogenous state variable representing the current position in the underlying. The exogenous coefficients in the solution are given by recursive formulas which can be calculated efficiently in Markov models. I illustrate effects of the partial execution risk in several examples.

Original languageEnglish
Pages (from-to)29-53
Number of pages25
JournalReview of Derivatives Research
Volume12
Issue number1
DOIs
Publication statusPublished - Apr 1 2009

Fingerprint

Mean-variance hedging
Dynamic programming
State variable
Hedging
Hedge
Hedging strategies
Markov model
Coefficients
Recursive formula
Assets
Mean-variance
Illiquid markets

All Science Journal Classification (ASJC) codes

  • Finance
  • Economics, Econometrics and Finance (miscellaneous)

Cite this

Dynamic programming and mean-variance hedging with partial execution risk. / Matsumoto, Koichi.

In: Review of Derivatives Research, Vol. 12, No. 1, 01.04.2009, p. 29-53.

Research output: Contribution to journalArticle

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