Non-cooperative dynamic games for general insurance markets

Boonen, Tim J.; Pantelous, Athanasios A.; Wu, Renchao

doi:10.1016/j.insmatheco.2017.12.001

Cited by 14 publications

(6 citation statements)

References 47 publications

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“…The theory of dynamic games is a powerful tool to model such sequential strategic interaction among selfish players, introduced by [1]. Discrete-time dynamic games with Markovian structure have been studied extensively to model many practical applications in both engineering and economics, such as as dynamic auctions [2], [3], security [4], markets [5], [6], traffic routing [7], [8], wireless systems [9], social learning [10], [11], oligopoliesi.e. competition among firms (e.g.…”

Section: Introductionmentioning

confidence: 99%

Master Equation for Discrete-Time Stackelberg Mean Field Games with single leader

Vasal¹,

Berry²

2022

Preprint

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In this paper, we consider a discrete-time Stackelberg mean field game with a leader and an infinite number of followers. The leader and the followers each observe types privately that evolve as conditionally independent controlled Markov processes. The leader commits to a dynamic policy and the followers best respond to that policy and each other. Knowing that the followers would play a mean field game based on her policy, the leader chooses a policy that maximizes her reward. We refer to the resulting outcome as a Stackelberg mean field equilibrium (SMFE). In this paper, we provide a master equation of this game that allows one to compute all SMFE. Based on our framework, we consider two numerical examples. First, we consider an epidemic model where the followers get infected based on the mean field population. The leader chooses subsidies for a vaccine to maximize social welfare and minimize vaccination costs. In the second example, we consider a technology adoption game where the followers decide to adopt a technology or a product and the leader decides the cost of one product that maximizes his returns, which are proportional to the people adopting that technology.

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Section: Introductionmentioning

confidence: 99%

Master Equation for Discrete-Time Stackelberg Mean Field Games with single leader

Vasal¹,

Berry²

2022

Preprint

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“…Concerning noncooperative games to model non-life insurance markets, in a static framework Dutang et al (2013) and Mourdoukoutas et al (2021) study one-period stochastic games to determine the optimal premium levels. In continuous time, Emms (2012) and Li et al (2021) propose N -player differential games in a deterministic framework, Boonen et al (2018) propose a N -player differential game by considering competition among each pair of insurers, based on a static concept proposed by Wu & Pantelous (2017). Asmussen et al (2019a,b) propose two-player differential games, where the premiums result from Nash or Stackelberg equilibria.…”

Section: Introductionmentioning

confidence: 99%

On a Markovian Game Model for Competitive Insurance Pricing

Mouminoux

Dutang

Loisel

et al. 2021

Methodol Comput Appl Probab

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In this paper, we extend the non-cooperative one-period game of Dutang et al. (2013) to model a non-life insurance market over several periods by considering the repeated (one-period) game. Using Markov chain methodology, we derive general properties of insurer portfolio sizes given a price vector. In the case of a regulated market (identical premium), we are able to obtain convergence measures of long run market shares. We also investigate the consequences of the deviation of one player from this regulated market. Finally, we provide some insights of long-term patterns of the repeated game as well as numerical illustrations of leadership and ruin probabilities.

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“…In a research, as an analyzing in the written form, the premium dynamic is modeled and analyzed thorough various game theory methods regarding the average market premium. Furthermore, the insurer equilibrium premium vitals in a rival market have been examined [18].…”

Section: Introductionmentioning

confidence: 99%

Game theoretic approach for flood risk management considering a financial model

Moosakhaani

Salimi

Sadatipour

et al. 2021

Environmental Engineering Research

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In process of flood risk management, there is usually conflict between the governments, insurance companies and people as players in sharing financial responsibilities, because of how calculate insurance premium, compensation and governmental assistances. In order to this conflict resolution, in this paper a new methodology is proposed based on game theoretic approach by using Nash equilibrium method, that for the first time, the payoff functions of insurance companies and government have been associated to each other. In this method, according to maximization of player's payoffs, the best response has been found and for the first time, comprehensive financial model has been developed for sharing players' financial responsibilities in flood risk management plans. In order to increase the accuracy of flood insurance calculations, the parameters of deductible and franchise have been applied. The key findings indicate, success of flood risk management plans depend on purchasing flood insurance with full coverage and government financial assistances simultaneously. The developed flood insurance plan has most sensitivity to parameters of deductible and insurance rate. This model could be utilized as practical and academic model in flood risk management. The applicability and efficiency of the methodology are examined in Northeast of Tehran as capital of Iran.

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Non-cooperative dynamic games for general insurance markets

Cited by 14 publications

References 47 publications

Master Equation for Discrete-Time Stackelberg Mean Field Games with single leader

Master Equation for Discrete-Time Stackelberg Mean Field Games with single leader

On a Markovian Game Model for Competitive Insurance Pricing

Game theoretic approach for flood risk management considering a financial model

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