基于信息修正的非期望效用模型

A Non-Expected Utility Model Based on Info-modification

人们对事件发生的可能性存在着主观判断。在不同的概率区间,人们对概率变化的敏感度是不一样的。传统的期望效用理论忽视了决策者对概率的主观反应,无法准确描述风险决策行为。基于信息修正的非期望效用模型,将客观概率转换成主观决策权重,可以弥补期望效用模型在捕捉决策者对概率主观反应方面的缺陷;同时,利用基于信息修正的非期望效用模型,通过量化人们在购买保险或股票时对风险的主观概率判断,可以对人们的保险需求和证券投资行为作出更好的解释或预测。

In this paper, we review the shortcomings of the application of expected utility theory and its improvements made by theoreticians-the development of non-expected utility theory, analyze the factors that affect decision-makers＇ judgments and information＇s modification for it, construct a decision-weighted function base on conditional probability and info-modification, transform objective probabilities to subjective decision weights, then develop a non-expected utility model based on these subjective decision weights. Such a model will betterinterpret and forecast the insurance need and security investment behavior, which is also the next research focus of the paper.