Optimal Reinsurance: A Risk Sharing Approach

Abstract

This paper proposes risk sharing strategies, which allow insurers to cooperate and diversify non-systemic risk. We deal with both deviation measures and coherent risk measures and provide general mathematical methods applying to optimize them all. Numerical examples are given in order to illustrate how efficiently the non-systemic risk can be diversified and how effective the presented mathematical tools may be. It is also illustrated how the existence of huge disasters may lead to wrong solutions of our optimal risk sharing problem, in the sense that the involved risk measure could ignore the existence of a non-null probability of "global ruin" after the design of the optimal risk sharing strategy. To overcome this caveat, one can use more conservative risk measures. The stability in the large of the optimal sharing plan guarantees that "the global ruin caveat" may be also addressed and solved with the presented methods

SOX2 promotes lineage plasticity and antiandrogen resistance in TP53 - and RB1 -deficient prostate cancer

“…SOX2 promotes lineage plasticity and antiandrogen resistance in TP53and RB1-deficient prostate cancer Ping Mu, 1 Zeda Zhang, 1,2 Matteo Benelli, 3 Wouter R. Karthaus, 1 Elizabeth Hoover, 1 Chi-Chao Chen, 4,5 John Wongvipat, 1 Sheng-Yu Ku, 6 Dong Gao, 1 Zhen Cao, 1,5 Neel Shah, 1,2 Elizabeth J. Adams, 1 Wassim Abida, 1 Philip A. Watson, 1 Davide Prandi, 3 Chun-Hao Huang, 4,5 Elisa de Stanchina, 7 Scott W. Lowe, 4,5,8 Leigh Ellis, 6 Himisha Beltran, 9,10 Mark A. Rubin, 9,10 David W. Goodrich, 6 Francesca Demichelis, 3,9 Charles L. Sawyers 1,8 * Some cancers evade targeted therapies through a mechanism known as lineage plasticity, whereby tumor cells acquire phenotypic characteristics of a cell lineage whose survival no longer depends on the drug target. We use in vitro and in vivo human prostate cancer models to show that these tumors can develop resistance to the antiandrogen drug enzalutamide by a phenotypic shift from androgen receptor (AR)-dependent luminal epithelial cells to AR-independent basal-like cells.…”

“…To determine whether the loss of TP53 function confers antiandrogen resistance, we introduced stable short hairpin RNAs (shRNAs) targeting TP53 into LNCaP/AR prostate cancer cells, a wild-type (WT) TP53 model that is highly sensitive to the next-generation antiandrogen enzalutamide (9). This model has previously revealed resistance mechanisms, such as AR mutation or glucocorticoid overexpression, that are now observed in patients (10,11). Although TP53 knockdown caused a modest reduction in enzalutamide sensitivity of LNCaP/AR cells grown in vitro, no effect was observed in another WT TP53 human prostate cancer model (CWR22Pc-EP) or in LNCaP/AR xenografts (Fig.…”

RNA-Seq of single prostate CTCs implicates noncanonical Wnt signaling in antiandrogen resistance

“…3A and table S5). The F876L mutation (Phe 876 replaced by Leu) in the ligand-binding domain, which converts the AR antagonist enzalutamide to a potential AR agonist (19,20), was not detected in any of the CTCs (<1 out of 32 CTCs with sufficient sequencing reads for mutational analysis). Thus, in our study, point mutations in AR known to be associated with altered signaling were uncommon in patients with CRPC, consistent with other reports (4,21).…”

Multi-Objective Stochastic Optimization Programs for a Non-Life Insurance Company under Solvency Constraints

“…In the actuarial context, the study conducted in [24] represents a first attempt to analyze and compare the capabilities of genetic programming and the particle swarm algorithm to find optimal solutions with respect to inspection algorithms for reinsurance problems (see also [25] for a precise definition). They concluded that the evolutionary algorithms are excellent options to find good solutions in short computation times.…”