scholarly journals Endowment effects in the risky investment game?

2021 ◽  
Author(s):  
Stein T. Holden ◽  
Mesfin Tilahun
Keyword(s):  
Expected Utility ◽  
Utility Theory ◽  
Expected Utility Theory ◽  
Initial Position ◽  
Risk Tolerance ◽  
Endowment Effect ◽  
Initial Endowment ◽  
Investment Game ◽  
Simple Tool ◽  
Risky Investment

AbstractThe risky investment game of Gneezy and Potters (Q J Econ 112(2):631–645, 1997) has been proposed as a simple tool to measure risk aversion in applied settings, especially attractive in settings where participants may have limited education. However, this game can produce a significant endowment effect (attached to the initial position), so that analysis of the behavior in this game should not be done in the Expected Utility Theory (EUT) framework. The paper illustrates this point, by showing that risk tolerance can be much higher when the initial endowment concerns a risky lottery.

scholarly journals A Prospect Theoretic Approach for Trust Management in IoT Networks under Manipulation Attacks

2020 ◽  
Author(s):  
Mehrdad Salimitari ◽  
Shameek Bhattacharjee ◽  
Mainak Chatterjee ◽  
Yaser Fallah
Keyword(s):  
Prospect Theory ◽  
Expected Utility ◽  
Utility Theory ◽  
Data Integrity ◽  
Expected Utility Theory ◽  
Trust Model ◽  
Aggregate Data ◽  
Risk Tolerance ◽  
Risk Attitudes ◽  
Theoretic Approach

<div>As Internet of Things (IoT) and Cyber-Physical systems become more ubiquitous in our daily lives, it necessitates the capability to measure the trustworthiness of the aggregate data from such systems to make fair decisions. However, the interpretation of trustworthiness is contextual and varies according to the risk tolerance attitude of the concerned application. In addition, there exist varying levels of uncertainty associated with an evidence upon which a trust model is built. Hence, the data integrity scoring mechanisms require some provisions to adapt to different risk attitudes and uncertainties.</div><div><br></div><div>In this paper, we propose a prospect theoretic framework for data integrity scoring that quantifies the trustworthiness of the collected data from IoT devices in the presence of adversaries who try to manipulate the data. In our proposed method, we consider an imperfect anomaly monitoring mechanism that tracks the transmitted data from each device and classifies the outcome (trustworthiness</div><div>of data) as not compromised, compromised, or undecided. These outcomes are conceptualized as a multinomial hypothesis of a Bayesian inference model with three parameters. These parameters are then used for calculating a utility value via prospect theory to evaluate</div><div>the reliability of the aggregate data at an IoT hub. In addition, to take into account different risk attitudes, we propose two types of fusion rule at IoT hub– optimistic and conservative.</div><div><br></div><div>Furthermore, we put forward asymmetric weighted moving average (AWMA) scheme to measure the trustworthiness of aggregate data in presence of On-Off attacks. The proposed framework is validated using extensive simulation experiments for both uniform and On-Off attacks. We show how trust scores vary under a variety of system factors like attack magnitude and inaccurate detection. In addition, we measure the trustworthiness of the aggregate data using the well-known expected utility theory and compare the results</div><div>with that obtained by prospect theory. The simulation results reveal that prospect theory quantifies trustworthiness of the aggregate data better than expected utility theory.</div>

scholarly journals A Prospect Theoretic Approach for Trust Management in IoT Networks under Manipulation Attacks

2020 ◽  
Author(s):  
Mehrdad Salimitari ◽  
Shameek Bhattacharjee ◽  
Mainak Chatterjee ◽  
Yaser Fallah
Keyword(s):  
Prospect Theory ◽  
Expected Utility ◽  
Utility Theory ◽  
Data Integrity ◽  
Expected Utility Theory ◽  
Trust Model ◽  
Aggregate Data ◽  
Risk Tolerance ◽  
Risk Attitudes ◽  
Theoretic Approach

<div>As Internet of Things (IoT) and Cyber-Physical systems become more ubiquitous in our daily lives, it necessitates the capability to measure the trustworthiness of the aggregate data from such systems to make fair decisions. However, the interpretation of trustworthiness is contextual and varies according to the risk tolerance attitude of the concerned application. In addition, there exist varying levels of uncertainty associated with an evidence upon which a trust model is built. Hence, the data integrity scoring mechanisms require some provisions to adapt to different risk attitudes and uncertainties.</div><div><br></div><div>In this paper, we propose a prospect theoretic framework for data integrity scoring that quantifies the trustworthiness of the collected data from IoT devices in the presence of adversaries who try to manipulate the data. In our proposed method, we consider an imperfect anomaly monitoring mechanism that tracks the transmitted data from each device and classifies the outcome (trustworthiness</div><div>of data) as not compromised, compromised, or undecided. These outcomes are conceptualized as a multinomial hypothesis of a Bayesian inference model with three parameters. These parameters are then used for calculating a utility value via prospect theory to evaluate</div><div>the reliability of the aggregate data at an IoT hub. In addition, to take into account different risk attitudes, we propose two types of fusion rule at IoT hub– optimistic and conservative.</div><div><br></div><div>Furthermore, we put forward asymmetric weighted moving average (AWMA) scheme to measure the trustworthiness of aggregate data in presence of On-Off attacks. The proposed framework is validated using extensive simulation experiments for both uniform and On-Off attacks. We show how trust scores vary under a variety of system factors like attack magnitude and inaccurate detection. In addition, we measure the trustworthiness of the aggregate data using the well-known expected utility theory and compare the results</div><div>with that obtained by prospect theory. The simulation results reveal that prospect theory quantifies trustworthiness of the aggregate data better than expected utility theory.</div>

scholarly journals Cumulative Prospect Theory Version with Fuzzy Values of Outcome Estimates

Risks ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 72
Author(s):  
Oleg Uzhga-Rebrov ◽  
Peter Grabusts
Keyword(s):  
Prospect Theory ◽  
Expected Utility ◽  
Utility Theory ◽  
Expected Utility Theory ◽  
Cumulative Prospect Theory ◽  
Development History ◽  
Decisions Under Risk ◽  
History Of ◽  
Main Factors ◽  
Theoretical Foundations

Choosing solutions under risk and uncertainty requires the consideration of several factors. One of the main factors in choosing a solution is modeling the decision maker’s attitude to risk. The expected utility theory was the first approach that allowed to correctly model various nuances of the attitude to risk. Further research in this area has led to the emergence of even more effective approaches to solving this problem. Currently, the most developed theory of choice with respect to decisions under risk conditions is the cumulative prospect theory. This paper presents the development history of various extensions of the original expected utility theory, and the analysis of the main properties of the cumulative prospect theory. The main result of this work is a fuzzy version of the prospect theory, which allows handling fuzzy values of the decisions (prospects). The paper presents the theoretical foundations of the proposed version, an illustrative practical example, and conclusions based on the results obtained.

Norm-Endorsement Utilitarianism and the Nature of Utility

1996 ◽  
Vol 12 (2) ◽  
pp. 165-182 ◽  
Author(s):  
Jonathan Baron
Keyword(s):  
Expected Utility ◽  
Utility Theory ◽  
Expected Utility Theory ◽  
Interpersonal Comparison ◽  
Moral Norms ◽  
Moral Principles ◽  
Future Goals ◽  
Equal Consideration

In this article, I shall suggest an approach to the justification of normative moral principles which leads, I think, to utilitarianism. The approach is based on asking what moral norms we would each endorse if we had no prior moral commitments. I argue that we would endorse norms that lead to the satisfaction of all our nonmoral values or goals. The same approach leads to a view of utility as consisting of those goals that we would want satisfied. In the second half of the article, I examine the implication of this view for several issues about the nature of utility, such as the use of past and future goals. The argument for utilitarianism is not completed here. The rest of it requires a defense of expected-utility theory, of interpersonal comparison, and of equal consideration (see Baron, 1993; Broome, 1991).

Housing Market Search Behavior and Expected Utility Theory: 1. Measuring Preferences for Housing

1982 ◽  
Vol 14 (5) ◽  
pp. 681-698 ◽  
Author(s):  
T R Smith ◽  
W A V Clark
Keyword(s):  
Los Angeles ◽  
Housing Market ◽  
Expected Utility ◽  
Utility Theory ◽  
House Price ◽  
Expected Utility Theory ◽  
Utility Functions ◽  
Future Search ◽  
Space Construction ◽  
Market Search

This is the first of two papers examining housing market search in a Los Angeles market. In this paper, we derive and analyze utility functions for housing for each individual in two groups of subjects. The utility functions are derived from an experimental setting, in which house price, floor space, construction quality, and neighborhood quality are varied. The functions are found to be essentially compatible with a linear model. They are used to predict the ratings of real houses and the ratings of the expected value of future search. These ratings are compared with actual ratings obtained from subjects during search. The results suggest that the actual or predicted ratings may be employed in a direct test of a simple expected utility theory of search, and further research along these lines appears justified.

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