Nash equilibria of Over-The-Counter bargaining for insurance risk redistributions: The role of a regulator

Boonen, Tim J.

doi:10.1016/j.ejor.2015.09.062

Cited by 17 publications

(10 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Very few papers in the literature consider the fact in Over-The-Counter trades, benefits from sharing risk are shared between the two parties. Some exceptions are Kihlstrom and Roth (1982), Schlesinger (1984), Aase (2009), Boonen et al (2012), Zhou et al (2015b), and Boonen (2016). All these authors consider the Nash bargaining solution.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Pricing in Reinsurance Bargaining With Comonotonic Additive Utility Functions

Boonen¹,

Tan²,

Zhuang

2016

ASTIN Bull.

Self Cite

View full text Add to dashboard Cite

Optimal reinsurance indemnities have widely been studied in the literature, yet the bargaining for optimal prices has remained relatively unexplored. Therefore, the key objective of this paper is to analyze the price of reinsurance contracts. We use a novel way to model the bargaining powers of the insurer and reinsurer, which allows us to generalize the contracts according to the Nash bargaining solution, indifference pricing and the equilibrium contracts. We illustrate these pricing functions by means of inverse-S shaped distortion functions for the insurer and the Value-at-Risk for the reinsurer.

show abstract

Section: Resultsmentioning

confidence: 99%

“…Non-cooperative characterizations of the asymmetric Nash bargaining solution are provided by, e.g., Britz et al (2010) and Miyakawa (2012). The Nash bargaining solution gained popularity in pricing reinsurance risk as well (see, e.g., Aase, 2009;Boonen et al, 2012;Zhou et al, 2015b;Boonen, 2016).…”

Section: There Exists An F Solving (4)mentioning

confidence: 99%

Pricing in Reinsurance Bargaining With Comonotonic Additive Utility Functions

Boonen¹,

Tan²,

Zhuang

2016

ASTIN Bull.

Self Cite

View full text Add to dashboard Cite

show abstract

“…This paper takes a "social planner" point of view. We do not model a negotiation process between the agents, as for instance in Boonen (2016). State prices, which are used to determine financial fairness, are assumed to be given.…”

Section: Introductionmentioning

confidence: 99%

The composite iteration algorithm for finding efficient and financially fair risk-sharing rules

Pazdera

Schumacher

Werker

2017

Journal of Mathematical Economics

View full text Add to dashboard Cite

The composite iteration algorithm for finding efficient and financially fair risk-sharing rules Pazdera, J.; Schumacher, J.M.; Werker, B.J.M. Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. AbstractWe consider the problem of finding an efficient and fair ex-ante rule for division of an uncertain monetary outcome among a finite number of von Neumann-Morgenstern agents. Efficiency is understood here, as usual, in the sense of Pareto efficiency subject to the feasibility constraint. Fairness is defined as financial fairness with respect to a predetermined pricing functional. We show that efficient and financially fair allocation rules are in one-to-one correspondence with positive eigenvectors of a nonlinear homogeneous and monotone mapping associated to the risk sharing problem. We establish relevant properties of this mapping. On the basis of this, we obtain a proof of existence and uniqueness of solutions via nonlinear Perron-Frobenius theory, as well as a proof of global convergence of the natural iterative algorithm. We argue that this algorithm is computationally attractive, and discuss its rate of convergence.

show abstract

“…Entries of new insurers and insurance products are not taken into consideration. Insurers avoid to set premium under cost level (Taylor, 1986(Taylor, , 1987Emms et al, 2007;Pantelous and Passalidou, 2013, 2015, 2016, and see the references therein). Thus, the case that p 1 i ≤ π 1 i is not considered in this paper.…”

Section: K Imentioning

confidence: 99%

Potential Games With Aggregation in Non-Cooperative General Insurance Markets

Pantelous

2016

ASTIN Bull.

View full text Add to dashboard Cite

In the global insurance market, the number of product-specific policies from different companies has increased significantly, and strong market competition has boosted the demand for a competitive premium. Thus, in the present paper, by considering the competition between each pair of insurers, an N-player game is formulated to investigate the optimal pricing strategy by calculating the Nash equilibrium in an insurance market. Under that framework, each insurer is assumed to maximise its utility of wealth over the unit time interval. With the purpose of solving a game of N-players, the best-response potential game with non-linear aggregation is implemented. The existence of a Nash equilibrium is proved by finding a potential function of all insurers' payoff functions. A 12-player insurance game illustrates the theoretical findings under the framework in which the best-response selection premium strategies always provide the global maximum value of the corresponding payoff function.

show abstract

Nash equilibria of Over-The-Counter bargaining for insurance risk redistributions: The role of a regulator

Cited by 17 publications

References 37 publications

Pricing in Reinsurance Bargaining With Comonotonic Additive Utility Functions

Pricing in Reinsurance Bargaining With Comonotonic Additive Utility Functions

The composite iteration algorithm for finding efficient and financially fair risk-sharing rules

Potential Games With Aggregation in Non-Cooperative General Insurance Markets

Contact Info

Product

Resources

About