The Impact of Probability Distortion On Decision-Making under Risk
Purpose: The aim of the article is to construct a behavioral model of decision-making under risk with distorted probabilities, to formulate a criterion of decision optimization in this model and to examine the impact of the probability distortion on the decision-making process. Design/Methodology/Approach: A critical review of the literature is conducted, focusing on issues related to decision-making models under risk, the principles of optimal decision selection, and the issue of probability distortion in the context of cognitive distortions. A behavioral model of decision-making under risk with distorted probabilities is constructed using the BMR model. A new behavioral measure of decision value — the subjective expected relative utility on a given level of probability distortion — is defined. Based on this measure, a preference relation over admissible decisions is introduced and an optimization criterion for decision-making under risk is formulated. The study examines the strength of probability distortion's influence on choices and highlights behavioral aspects of individual decision-making under risk, including the roles of regret and satisfaction accompanying the decision process. Findings: The main results of the research are: construction BMRPD model (behavioral model of decision-making under risk with distorted probabilities); defining a new behavioral measure of decision value - the subjective expected relative utility on a given level of probability distortion (SERU); formulation, based on this measure, the principle for selecting the optimal decision under risk by an individual decision-maker who, under the influence of emotions and cognitive distortions, may distort the probabilities of payoff. Additionally, the properties of the probability distortion function are described. The results of choosing the optimal decision in a behavioral model with probability distortions (BMRPD model) differ from the results of choosing without distortions. The strength of the distortions also influences the outcome of the choice. Practical Implications: The results of the research can be used to study and predict investors’ behavior on the stock market, as well as to study the decisions of lottery players. They can also be used to construct a behavioral decision portfolio. Originality/Value: The paper contains the author’s original research results. The introduction of new behavioral measures for assessing decisions under risk allows for a better understanding of the decisions made by individual decision-makers, which may seem irrational based on classical theories such as utility maximization theory.