Findings from Zhejiang University Update Knowledge of Insurance Economics (Optimal multivariate quota-share reinsurance: A nonparametric mean-CVaR…

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Findings from Zhejiang University Update Knowledge of Insurance Economics (Optimal multivariate quota-share reinsurance: A nonparametric mean-CVaR framework)

By a News Reporter-Staff News Editor at Insurance Weekly News -- Researchers detail new data in Economics - Insurance Economics. According to news reporting out of Hangzhou, People's Republic of China, by VerticalNews editors, research stated, "In this paper, the Conditional Value-at-Risk (CVaR) is adopted to measure the total loss of multiple lines of insurance business and two nonparametric estimation methods are introduced to explore the optimal multivariate quota-share reinsurance under a mean-CVaR framework. While almost all the existing literature on optimal reinsurance are based on a probabilistic derivation, the present paper relies on a statistical analysis."

Funders for this research include Natural Sciences and Engineering Research Council of Canada, Society of Actuaries Centers of Actuarial Excellence Research, Fundamental Research Funds for the Central Universities, National Social Science Foundation of China, Zhejiang Provincial Natural Science Foundation.

Our news journalists obtained a quote from the research from Zhejiang University, "The proposed optimal reinsurance models are directly formulated on empirical data and no explicit distributional assumption on the underlying risk vector is required. The resulting nonparametric reinsurance models are convex and computationally amenable, circumventing the difficulty of computing CVaR of the sum of a generally dependent random vector. Statistical consistency of the resulting estimators for the best CVaR is established for both nonparametric models, allowing empirical data to be generated from any stationary process satisfying strong mixing conditions."

According to the news editors, the research concluded: "Finally, numerical experiments are presented to show that a routine bootstrap procedure can capture the distributions of the resulting risk measures well for independent data."

For more information on this research see: Optimal multivariate quota-share reinsurance: A nonparametric mean-CVaR framework. Insurance Mathematics & Economics, 2017;72():197-214. Insurance Mathematics & Economics can be contacted at: Elsevier Science Bv, PO Box 211, 1000 Ae Amsterdam, Netherlands.

Our news journalists report that additional information may be obtained by contacting H.Z. Sun, Zhejiang University, Sch Math Sci, Hangzhou 310027, Zhejiang, People's Republic of China. Additional authors for this research include C.G. Weng and Y. Zhang.

Keywords for this news article include: Hangzhou, People's Republic of China, Asia, Insurance Economics, Economics, Zhejiang University.