Human Behavior & Game Theory eJournal最新文献_第4页

Pricing in a Competitive Stochastic Insurance Market 竞争随机保险市场中的定价

Human Behavior & Game Theory eJournal Pub Date : 2020-09-02 DOI: 10.2139/ssrn.3685009

Fotios Mourdoukoutas, T. Boonen, B. Koo, A. Pantelous

{"title":"Pricing in a Competitive Stochastic Insurance Market","authors":"Fotios Mourdoukoutas, T. Boonen, B. Koo, A. Pantelous","doi":"10.2139/ssrn.3685009","DOIUrl":"https://doi.org/10.2139/ssrn.3685009","url":null,"abstract":"Abstract This paper studies a one-period stochastic game to determine the optimal premium strategies of non-life insurers in a competitive market. Specifically, the optimal premium strategy is determined by the Nash equilibrium of an n -player game, in which each player is assumed to maximise the expected utility of terminal wealth. The terminal wealth is stochastic, since the number of policies and the size of claims are considered to be random variables. The total loss of each insurer is described by the collective risk model. The expected number of policies is affected by all the premiums in the market and further investigated by two distinct demand functions. Both models have an exponential functional form, that is characterised by market and price sensitivity parameters. The demand in the first model is zero for premiums above a given threshold, whereas the second model does not include such restriction. The pure strategy Nash equilibrium premiums are given as solutions to constrained optimisation problems. For the first model we prove the existence and uniqueness of a pure strategy Nash equilibrium, whereas for the second model we provide a formula when it exists. Two numerical examples are provided to illustrate the applicability of our findings.","PeriodicalId":322168,"journal":{"name":"Human Behavior & Game Theory eJournal","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126663153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Human Behavior & Game Theory eJournal Pub Date : 2020-08-30 DOI: 10.2139/ssrn.3686145

Nabil Afodjo, Roland Pongou

引用次数: 0

CEO Overconfidence, Moral Hazard, and Investment 过度自信、道德风险与投资

Human Behavior & Game Theory eJournal Pub Date : 2020-08-25 DOI: 10.2139/ssrn.3680313

Ramji Balakrishnan, George Drymiotes, S. Sivaramakrishnan, J. Tian

{"title":"CEO Overconfidence, Moral Hazard, and Investment","authors":"Ramji Balakrishnan, George Drymiotes, S. Sivaramakrishnan, J. Tian","doi":"10.2139/ssrn.3680313","DOIUrl":"https://doi.org/10.2139/ssrn.3680313","url":null,"abstract":"Using an agency theory framework, we examine the effect of managerial overconfidence on the interaction between planning and control problems. We consider a typical setting in which a manager makes an investment decision involving project selection and a production decision to implement the chosen project. Thus, adverse selection and moral hazard problems affect different facets of management decision making, which allows us to examine how overconfidence affects the interaction between adverse selection and moral hazard. We show that overall welfare implications depend on the kind of overconfidence: productivity-related or state-related. When the agent overestimates the productivity of his effort, the principal can actually exploit the overconfidence and induce him to provide more effort at lower cost. However, overconfidence can either exacerbate an existing overinvestment problem or it can mitigate an existing underinvestment problem. We show that productivity-related overconfidence unequivocally improves the principal's welfare. On the contrary, state-related overconfidence aggravates the effort incentive problem but can ameliorate the underinvestment problem. Overall, state-related overconfidence decreases investor welfare, consistent with the negative connotation we often ascribe to overconfidence.","PeriodicalId":322168,"journal":{"name":"Human Behavior & Game Theory eJournal","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124870278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Contracts as Reference Points: A Replication 契约作为参考点:复制

Human Behavior & Game Theory eJournal Pub Date : 2020-08-13 DOI: 10.2139/ssrn.3696458

Svenja Hippel, Sven Hoeppner

引用次数: 2

Inattentive Inference 粗心的推理

Human Behavior & Game Theory eJournal Pub Date : 2020-07-22 DOI: 10.2139/ssrn.3658112

Thomas Graeber

引用次数: 14

Nonatomic Game with General Preferencees on Returns 具有一般收益偏好的非原子博弈

Human Behavior & Game Theory eJournal Pub Date : 2020-07-16 DOI: 10.2139/ssrn.3653306

Jian Yang

引用次数: 0

Uncertainty and Decision-Making During a Crisis: How to Make Policy Decisions in the COVID-19 Context? 危机中的不确定性与决策:如何在2019冠状病毒病背景下做出决策?

Human Behavior & Game Theory eJournal Pub Date : 2020-07-08 DOI: 10.2139/ssrn.3647188

L. Berger, Nicolas Berger, V. Bosetti, I. Gilboa, L. Hansen, C. Jarvis, M. Marinacci, Richard D. Smith

引用次数: 19

What Personal Information Can a Consumer Facial Image Reveal? Implications for Marketing ROI and Consumer Privacy 消费者的面部图像可以透露哪些个人信息?市场投资回报率和消费者隐私的含义

Human Behavior & Game Theory eJournal Pub Date : 2020-06-01 DOI: 10.2139/ssrn.3616470

Yegor Tkachenko, K. Jedidi

{"title":"What Personal Information Can a Consumer Facial Image Reveal? Implications for Marketing ROI and Consumer Privacy","authors":"Yegor Tkachenko, K. Jedidi","doi":"10.2139/ssrn.3616470","DOIUrl":"https://doi.org/10.2139/ssrn.3616470","url":null,"abstract":"Massive availability of individuals’ facial images through online uploads and CCTV surveillance, combined with lacking regulation, presents potential for companies to obtain richer consumer data -- at the risk of privacy violations through exposure of personal information in such images. Building on rich survey data and supermarket video and receipt information, we provide systematic evaluation of relative predictability of different types of personal information -- through deep learning on facial images. We find facial images provide versatile statistical signals on individual's behaviors, preferences, character, personality, and beliefs. A large part of such predictive power is attributable to basic demographics extracted from the face. However, image artifacts, observable facial features, and deep image features extracted by a neural net all contribute to prediction accuracy beyond demographics. Using empirical evidence, a decision theory proof, and a simulation study, we argue such incremental information can meaningfully increase return on investment (ROI) when used for targeting. The limited accuracy of predictions from facial images attenuates the privacy risks to some degree, however, the variety of signals from a facial image is surprising. Prejudice caused by human decision makers' exposure to such statistical information is a substantial concern. We hope our results and the novel data we release with this work inspire research in the emerging area of facial analysis.","PeriodicalId":322168,"journal":{"name":"Human Behavior & Game Theory eJournal","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123470103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Survey Evidence on Habit Formation: Existence, Specification, and Implication 习惯形成的调查证据:存在、规范和含义

Human Behavior & Game Theory eJournal Pub Date : 2020-05-14 DOI: 10.2139/ssrn.3685591

Jiannan Zhou

引用次数: 2

Hyperopic Loss Aversion 远视损失厌恶

Human Behavior & Game Theory eJournal Pub Date : 2020-04-21 DOI: 10.2139/ssrn.3582050

Jan S. Krause, P. Ring, Ulrich Schmidt

{"title":"Hyperopic Loss Aversion","authors":"Jan S. Krause, P. Ring, Ulrich Schmidt","doi":"10.2139/ssrn.3582050","DOIUrl":"https://doi.org/10.2139/ssrn.3582050","url":null,"abstract":"The literature reports a tendency that future losses are discounted less than future gains, the so-called sign effect in intertemporal decision making. In this article, we study implications of the sign effect on risk taking: If future losses are discounted less than future gains, mixed lotteries involving both gains and losses should become less attractive when payments are delayed into the future. We refer to this phenomenon as Hyperopic Loss Aversion and provide experimental evidence for it: First, we provide a robust conceptual replication of the sign effect where we find non-positive discount rates for losses. Second, we confirm our hypothesis that mixed lotteries become less attractive over time. This effect can be attributed to Hyperopic Loss Aversion in our design, as a delay does not change the valuation of either pure gain and pure loss lotteries. Finally, we apply the notion of Hyperopic Loss Aversion to investment decisions and show that it offers a novel behavioral explanation for the equity premium puzzle. While our empirical analyses are entirely model-free, we also introduce a theoretical basis to analyze Hyperopic Loss Aversion. Our model, termed Discounted Prospect Theory, can be regarded as a natural extension of Prospect Theory to the intertemporal domain.","PeriodicalId":322168,"journal":{"name":"Human Behavior & Game Theory eJournal","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121603536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1