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Generalisation of Hajek’s Stochastic Comparison Results to Stochastic Sums

Jörg Kampen

International Journal of Stochastic Analysis2016https://doi.org/10.1155/2016/1018509article
ABDC B
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0.40

What the paper says

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.

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https://doi.org/https://doi.org/10.1155/2016/1018509

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@article{jörg2016,
  title        = {{Generalisation of Hajek’s Stochastic Comparison Results to Stochastic Sums}},
  author       = {Jörg Kampen},
  journal      = {International Journal of Stochastic Analysis},
  year         = {2016},
  doi          = {https://doi.org/https://doi.org/10.1155/2016/1018509},
}

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Generalisation of Hajek’s Stochastic Comparison Results to Stochastic Sums

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Evidence weight

0.40

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.36 × 0.4 = 0.14
M · momentum0.20 × 0.15 = 0.03
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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