New Applied Probability Research Findings from University of Leicester Reported (Optimal Reinsurance Via Dirac-feynman Approach)

2019 MAY 30 (NewsRx) -- By a News Reporter-Staff News Editor at Math Daily News -- Fresh data on Mathematics - Applied Probability Research are presented in a new report. According to news reporting originating from Leicester, United Kingdom, by NewsRx correspondents, research stated, “In this paper, the Dirac-Feynman path calculation approach is applied to analyse finite time ruin probability of a surplus process exposed to reinsurance by capital injections. Several reinsurance optimization problems on optimum insurance and reinsurance premium with respect to retention level are investigated and numerically illustrated.”

Our news editors obtained a quote from the research from the University of Leicester, “The retention level is chosen to decrease the finite time ruin probability and to guarantee that reinsurance premium covers an average of overall capital injections. All computations are based on Dirac-Feynman path calculation approach applied to the convolution type operators perturbed by Injection operator (shift type operator).”

According to the news editors, the research concluded: “In addition, the effect of the Injection operator on ruin probability is analysed.”

For more information on this research see: Optimal Reinsurance Via Dirac-feynman Approach. Methodology And Computing In Applied Probability, 2019;21(2):647-659. Methodology And Computing In Applied Probability can be contacted at: Springer, Van Godewijckstraat 30, 3311 Gz Dordrecht, Netherlands. (Springer - www.springer.com; Methodology And Computing In Applied Probability - http://www.springerlink.com/content/1387-5841/)

The news editors report that additional information may be obtained by contacting M. Tamturk, University of Leicester, Dept. of Mathematics, Leicester LE1 7RH, Leics, United Kingdom.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1007/s11009-018-9674-8. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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