Generalisation of Hajek’s Stochastic Comparison Results to Stochastic Sums

Jörg Kampen

International Journal of Stochastic Analysis, 2016, vol. 2016, 1-6

Abstract:

Hajek’s univariate stochastic comparison result is generalised to multivariate stochastic sum processes with univariate convex data functions and for univariate monotonic nondecreasing convex data functions for processes with and without drift, respectively. As a consequence strategies for a class of multivariate optimal control problems can be determined by maximizing variance. An example is passport options written on multivariate traded accounts. The argument describes a narrow path between impossibilities of generalisations to jump processes or impossibilities of more general data functions.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnijsa:1018509

DOI: 10.1155/2016/1018509

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