{"title":"Exploring Risk Sharing in Stochastic Exchange Networks","authors":"Arnaud Z. Dragicevic","doi":"10.1109/TCSS.2024.3508803","DOIUrl":null,"url":null,"abstract":"This study examines the dynamics of bargaining in a social system that incorporates risk sharing through exchange network models and stochastic matching between agents. The analysis explores three scenarios: convergent expectations, divergent expectations, and social preferences among model players. The study introduces stochastic shocks through a Poisson process, which can disrupt coordination within the decentralized exchange mechanism. Despite these shocks, agents can employ a risk-sharing protocol utilizing Pareto weights to mitigate their effects. The model outcomes do not align with the generalized Nash bargaining solutions across all scenarios. However, over a sufficiently long time frame, the dynamics consistently converge to a fixed point that slightly deviates from the balanced outcome or Nash equilibrium. This minor deviation represents the risk premium necessary for hedging against mutual risk. The risk premium is at its minimum in the scenario with convergent expectations and remains unchanged in the case involving social preferences.","PeriodicalId":13044,"journal":{"name":"IEEE Transactions on Computational Social Systems","volume":"12 3","pages":"1181-1192"},"PeriodicalIF":4.5000,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Computational Social Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10813572/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
引用次数: 0
Abstract
This study examines the dynamics of bargaining in a social system that incorporates risk sharing through exchange network models and stochastic matching between agents. The analysis explores three scenarios: convergent expectations, divergent expectations, and social preferences among model players. The study introduces stochastic shocks through a Poisson process, which can disrupt coordination within the decentralized exchange mechanism. Despite these shocks, agents can employ a risk-sharing protocol utilizing Pareto weights to mitigate their effects. The model outcomes do not align with the generalized Nash bargaining solutions across all scenarios. However, over a sufficiently long time frame, the dynamics consistently converge to a fixed point that slightly deviates from the balanced outcome or Nash equilibrium. This minor deviation represents the risk premium necessary for hedging against mutual risk. The risk premium is at its minimum in the scenario with convergent expectations and remains unchanged in the case involving social preferences.
期刊介绍:
IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.