TY - JOUR
T1 - Dynamic programming and mean-variance hedging with partial execution risk
AU - Matsumoto, Koichi
N1 - Funding Information:
Acknowledgements I wish to thank Professor Shigeo Kusuoka for helpful discussions and comments. I am deeply grateful to Professor Aleš Cˇ erný for valuable advice and for assistance in revising the paper. I also thank the participants of Workshop and Mid Term Conference on Advanced Mathematical Methods for Finance, for useful comments. This research was partially supported by the Ministry of Education, Science, Sports and Culture, Grant-in-Aid for Young Scientists (B), 19740051.
PY - 2009/4
Y1 - 2009/4
N2 - 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.
AB - 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.
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U2 - 10.1007/s11147-009-9033-6
DO - 10.1007/s11147-009-9033-6
M3 - Article
AN - SCOPUS:67349267303
SN - 1380-6645
VL - 12
SP - 29
EP - 53
JO - Review of Derivatives Research
JF - Review of Derivatives Research
IS - 1
ER -