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The increased volume of rumors and attention on related topics during the COVID-19 pandemic have had a significant negative social impact. To combat rumors, it is crucial to study the actors involved in their spread. In this study, we first introduce prospect theory and construct an evolutionary game model between network operators and government regulators. We investigate collusion between network operators and Internet rumormongers as well as the regulatory behavior of government agencies. Second, we use prospect value to replace traditional expected utility to construct a profit prospect matrix and apply the dynamic replicator equation to analyze the equilibrium stability of the model. The stability conditions of the game between the two parties are closely related to the government's regulatory costs, and the strength of government punishment after collusion is detected. Finally, we propose relevant countermeasures against collusion problems during the network rumor control period. [ABSTRACT FROM AUTHOR]

It remains a pressing concern to understand how neural computations relate to risky decisions. However, most observations of brain-behavior relationships in the risk-taking domain lack a rigorous computational basis or fail to emulate of the dynamic, sequential nature of real-life risky decision-making. Recent advances emphasize the role of neural prediction error (PE) signals. We modeled, according to prospect theory, the choices of n = 43 human participants (33 females, 10 males) performing an EEG version of the hot Columbia Card Task, featuring rounds of sequential decisions between stopping (safe option) and continuing with increasing odds of a high loss (risky option). Single-trial regression EEG analyses yielded a subjective value signal at centroparietal (300-700 ms) and frontocentral (>800 ms) electrodes and in the delta band, as well as PE signals tied to the feedback-related negativity, P3a, and P3b, and in the theta band. Higher risk preference (total number of risky choices) was linked to attenuated subjective value signals but increased PE signals. Higher P3-like activity associated with the most positive PE in each round predicted stopping in the present round but not risk-taking in the subsequent round. Our findings indicate that decreased representation of decision values and increased sensitivity to winning despite low odds (positive PE) facilitate risky choices at the subject level. Strong neural responses when gains are least expected (the most positive PE on each round) adaptively contribute to safer choices at the trial-by-trial level but do not affect risky choice at the round-by-round level. [ABSTRACT FROM AUTHOR]

This study investigated the interplay between exit selection models and local pedestrian movement patterns within floor field frameworks. Specifically, this investigation analysed the performance of a multinomial logit exit choice model, incorporating both expected utility theory and cumulative prospect theory frameworks when coupled with three distinct local-level pedestrian movement models (FF-Von Neumann, FF-Moore, and NSFF). The expected utility theory framework considers the deterministic component as a linear relationship, while the cumulative prospect theory framework further considers the decision-maker's risky attitudes by transforming objective terms into subjective terms using a power value function. The core objective was to comprehend how local movement dynamics, as represented by the floor field models, influence decision-making during exit selection. Comparative analyses revealed intriguing variations between the three local models, despite their shared expected utility theory-based exit choice framework. These discrepancies stemmed from the diverse pedestrian trajectory behaviours generated by each model. Consequently, these local dynamics impacted the decision-maker's assessment of critical factors, such as the number of evacuees close to the decision-maker ( N C D M ) and the number of evacuees close to an exit ( N C E ), which the exit choice model incorporates. These assessments, in turn, significantly affected higher-level decision-making. The integration of the three models with the multinomial logit exit choice model, using either cumulative prospect theory and expected utility theory frameworks, further strengthened the observed bilateral relationship. While the specific nature of this relationship varied depending on the chosen framework and its implementation details, these consistent findings demonstrate the robustness of the results. This reinforced the influence of local-level pedestrian dynamics on higher-level exit selection, highlighting the importance of accurate crowd dynamics modelling, especially when advanced exit choice models consider local movement factors. [ABSTRACT FROM AUTHOR]

This paper investigates a dynamic liability-driven investment policy for defined-benefit (DB) plans by incorporating the loss aversion of a sponsor, who is assumed to be more sensitive to underfunding than overfunding. Through the lens of prospect theory, we first set up a loss-aversion utility function for a sponsor whose utility depends on the funding ratio in each period, obtained from stochastic processes of pension assets and liabilities. We then construct a multi-horizon dynamic control optimization problem to find the optimal investment strategy that maximizes the expected utility of the plan sponsor. A genetic algorithm is employed to provide a numerical solution for our nonlinear dynamic optimization problem. Our results suggest that the overall paths of the optimal equity allocation decline as the age of a plan participant reaches retirement. We also find that the equity portion of the portfolio increases when a sponsor is less loss-averse or the contribution rate is lower. [ABSTRACT FROM AUTHOR]

Behavioral welfare economics usually aims at mere means paternalism, helping agents better pursue their own goals. This paper discusses one initially promising way to inform policies addressed at agents who violate expected utility theory (EUT), namely what I call "CPT debiasing." I argue that this approach is problematic even if we grant the normative authority of EUT, the descriptive adequacy of CPT (cumulative prospect theory), and the general acceptability of means paternalism. First, it is doubtful whether the CPT utility function measures what its proponents intend. Second, by imposing risk neutrality on agents, the approach involves a more problematic paternalism. [ABSTRACT FROM AUTHOR]

In economics, the Expected Utility (EU) model is the normative benchmark for decision making under risk. However, empirical studies have shown that many behavioural phenomena are inconsistent with the predictions of this model. Observing empirical evidence, behavioural economics has demonstrated that people do not always make rational, or optimal, decisions, even if they have the information and tools with which to do so. People's choices are influenced by their emotions and impulsiveness, and depend on their environment and circumstances (context): overconfidence, loss aversion, and self-control are the main statements in behavioural economics. Starting from past studies concerning the use of multi-criteria method based on prospect theory for describing people behavior (Gomes and Lima 1991), this paper aims at proposing a multi-criteria method as a tool to model some behavioural anomalies. It begins by analysing some decision problems proposed in the literature (Kahneman and Tversky 1979), showing that people's preferences may violate some of the axioms of the EU model. Then, it proposes a multi-criteria approach to model human behaviour in these problems, that is, when emotional factors and cognitive biases influence people's choices: e.g., the certainty effect and the reflection effect. Among several multi-critria methods, the ELimination Et Choix Traduisant la REalité (ELECTRE) method is used due to its main features: it allows dealing with positive and negative reasons in order to model the preferences, including with heterogeneous scales; its preference and indifference thresholds allow taking into account an imperfect knowledge of the data; no systematic compensation exists between "gains" and "losses". The results show that the ELECTRE III method provides the same preferences expressed by the majority of respondents in the experiments considered. In other words, a multi-criteria tool accounts for some behavioural anomalies, in particular, those relating to certainty and reflection effects. [ABSTRACT FROM AUTHOR]

We present a descriptive model of choice derived from neuroscientific models of efficient value representation in the brain. Our basic model, a special case of Expected Utility Theory, can capture a number of behaviors predicted by Prospect Theory. It achieves this with only two parameters: a time-indexed "payoff expectation" (reference point) and a free parameter we call "predisposition". A simple extension of the model outside the domain of Expected Utility also captures the Allais Paradox. Our models shed new light on the computational origins and evolution of risk attitudes and aversion to outcomes below reward expectation (reference point). It delivers novel explanations of the endowment effect, the observed heterogeneity in probability weighting functions, and the Allais Paradox, all with fewer parameters and higher descriptive accuracy than Prospect Theory. [ABSTRACT FROM AUTHOR]

Purpose -- This paper aims to provide empirical evidence for using the prospect theory (PT) basic assumptions in the Argentine context. Mainly, this study analysed the financial decision-making process in students of the economic-administrative academic area of two universities, one public and one private, in Córdoba. Design/methodology/approach -- The analysis methodology included (1) the descriptive statistical analysis to identify the presence of the certainty, reflection and isolation effects; (2) the construction of a set of indicators on the application of the PT; (3) the chi-squared independence test, to determine if the decisions made are independent of the degree course taken; (4) the non-parametric Kruskal--Wallis test, to determine if the decisions made by individuals vary according to the semesters taken or students' levels of progress; and (5) the non-parametric Mann--Whitney test, to determine if there are differences between the decisions made by men and women. Findings -- The empirical results provided evidence on the effects of certainty, reflection and isolation in both universities, concluding that the study participants make financial decisions in situations of uncertainty based more on PT than on expected utility theory. Originality/value -- This study contributes to the empirical evidence in a different Latin-American context, confirming that individuals make financial decisions based on the PT independently of their degree course, semester, level of advance, gender or the kind of university where they belong (public or private) [ABSTRACT FROM AUTHOR]

This review looks at the development of decision science and behavioral economics, tracing the chronological progression of these disciplines and their symbiotic fusion in elucidating our comprehension of economic choices. It starts by discussing the limitations of traditional economic theories that assume rational and profitmaximizing behavior, highlighting the need for a more empirically anchored approach. The paper traces the development of decision theory amidst uncertainty, beginning with Blaise Pascal's notion of expected value, progressing to Daniel Bernoulli's expected utility, and later formalized by John von Neumann and Oskar Morgenstern. This journey culminates in the contributions of Daniel Kahneman and Amos Tversky, who introduced the concept of subjective expected utility. The paper acknowledges the inclusion of uncertainty surrounding delayed payoffs and discusses the role of cognitive biases and heuristics--mental shortcuts--in decisionmaking, showing how they affect our economic choices. The authors also show how these insights have been used in real-world settings, such as nudging, a technique used to subtly guide one's behavior. [ABSTRACT FROM AUTHOR]

This study supports the use of behavioural finance to explain the popularity of portfolio insurance. Portfolio insurance strategies are important financial solutions sold to institutional and individual investors that protect against downside risk while maintaining some upside valuation potential. The way some of these strategies are engineered has been criticised and portfolio insurance itself blamed for increasing market volatility in depressed markets. Despite this, investors keep on buying portfolio insurance that keeps its solid market share. This study contributes to understand the phenomenon. We compare individual investors' decision using two distinct frameworks: expected utility theory and behavioural theories. Based upon Monte Carlo simulation techniques we compare portfolio insurance strategies against uninsured basic benchmark strategies, for a wide variety of market scenarios. We conclude that cumulative prospect theory may be a viable framework to explain the popularity of portfolio insurance. However, among portfolio insurance strategies, naïve strategies seem to be preferable to most commonly traded strategies. [ABSTRACT FROM AUTHOR]

A speculative agent with prospect theory preference chooses the optimal time to purchase and then to sell an indivisible risky asset to maximise the expected utility of the round-trip profit net of transaction costs. The optimisation problem is formulated as a sequential optimal stopping problem, and we provide a complete characterisation of the solution. Depending on the preference and market parameters, the optimal strategy can be "buy and hold", "buy low, sell high", "buy high, sell higher" or "no trading". Behavioural preference and market friction interact in a subtle way which yields surprising implications on the agent's trading patterns. For example, increasing the market entry fee does not necessarily curb speculative trading, but instead may induce a higher reference point under which the agent becomes more risk-seeking and in turn is more likely to trade. [ABSTRACT FROM AUTHOR]

Low insurance take‐up in low‐income populations is not easily explained by the standard single‐period expected utility model of insurance that overlooks the relevance of time preference when liquidity is constrained. We design field survey instruments to elicit quasi‐hyperbolic time preferences, as well as prospect theory risk preferences, and use them to examine whether time preferences explain health insurance behavior of low‐income Filipinos. Consistent with theory, those with stronger parameterized time preference are less likely to insure and the partial association is most pronounced at low wealth where liquidity is most likely to be constrained. Among those with better understanding of insurance, lower take‐up is also associated with present bias. We do not find that insurance is significantly associated with risk preferences. [ABSTRACT FROM AUTHOR]

When investing in new stocks, it is difficult to predict returns and risks in a general way without the support of historical data. Therefore, a portfolio optimization model with an uncertain rate of return is proposed. On this basis, prospect theory is used for reference, and then the uncertain return portfolio optimization model is established from the perspective of expected utility maximization. An improved gray wolf optimization (GWO) algorithm is designed because of the complex nonsmooth and nonconcave characteristics of the model. The results show that the GWO algorithm is superior to the traditional particle swarm optimization algorithm and genetic algorithm. [ABSTRACT FROM AUTHOR]

The literature suggests that probability weighting and choice set dependence influence risky choices. However, their relative importance remains an open question. We present a joint test that uses binary choices between lotteries provoking Common Consequence and Common Ratio Allais Paradoxes and manipulates their joint payoff distribution. We show non-parametrically that probability weighting and choice set dependence both play a role at describing aggregate choices. To parsimoniously account for heterogeneity, we also estimate a structural model using a finite mixture approach. The model uncovers substantial heterogeneity and classifies subjects into three types: 38% Prospect Theory types whose choices are predominantly driven by probability weighting, 34% Salience Theory types whose choices are predominantly driven by choice set dependence, and 28% Expected Utility Theory types. The model predicts type-specific differences in the frequency of preference reversals out-of-sample, i.e., in choices with a different context than the ones used for estimating the model. Moreover, the out-of-sample predictions indicate that the choice context shapes the influence of choice set dependence. [ABSTRACT FROM AUTHOR]

In a series of experiments, we provide evidence that people pay special attention to the probability of losing. We first analyze this behavior in the typically used one-shot choice tasks. We then extend our analysis to repeated decisions in choice tasks, as well as allocation and investment tasks. Additionally, we test both decision making under risk and under gradually removed uncertainty, as with decisions from experience. Our findings of explicit attention to loss probabilities contradict the predictions of normative and descriptive decision theories, such as Expected Utility Theory and (Cumulative) Prospect Theory. We suggest a value function with a jump rather than a kink at the reference point, which separates gains and losses. [ABSTRACT FROM AUTHOR]

Harry Markowitz is widely recognized to be the father of portfolio theory. But, for unknown reasons, his substantial contributions to utility theory are less well-known. Daniel Bernoulli is widely renowned for explaining the Saint Petersburg paradox. Most people recognize Adam Smith as being the father of capitalism. Some people are aware that Carl Menger (1840–1921) was one of the first to discuss (in German) diminishing marginal utility. Jules Dupuit (1804–1866) distinguished between total utility and marginal utility and, in the process, he went on to discover the consumers’ surplus. Although it is not widely recognized, Herman Heinrich Gossen (1810–1858) was the first economists to explain that the fundamental principle of marginal utility theory is that a person maximizes his utility when he distributes his available money among the various goods so that he obtains the same amount of satisfaction from the last unit of money spent on each different commodity. After explaining the Saint Petersburg paradox earlier in his career comma, Daniel Bernoulli later brought many utility suggestions together into one tidy package, and even went on to suggest that decision-maker’s decisions can probably be best represented by the logarithmic utility function. Each one of the previous contributions to utility theory constitutes a significant improvement in the previous theory. But in 1952 Harry Markowitz published several suggestions that each represented a significant advancement to the existing utility theory. The value of Markowitz’s suggestions was acknowledged in 1979 and 1992 by two psychologists named Daniel Kahneman and Amos Tversky when they introduced their prospect theory. These co-authors list and discuss several of Markowitz’s contributions to expected utility theory in their 1979 prospect theory paper. [ABSTRACT FROM AUTHOR]

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Prospect Theory, proposed and developed by Kahneman and Tversky, demonstrated that people do not make rational decisions based on expected utility, but are instead biased by specific cognitive tendencies leading to neglect, under- or over- consider information, depending on the context of presentation. In this vein, the present paper focuses on whether and how individual decision-making attitudes are prone to change in the presence of globally challenging events. We ran three partial replications of the Kahneman and Tversky (1979) paper, focusing on a set of eight prospects, after a terror attack (Paris, November 2015, 134 subjects) and during the Covid-19 pandemic, both during the first lockdown in Italy (Spring 2020, 176 subjects) and after the first reopening (140 subjects). The results confirm patterns of choice characterizing uncertain times, as shown by previous literature. In particular, we note significant increase of risk aversion, both in the gain and in the loss domains, that consistently emerged in the three replications. Given the nature of our sample, and the heterogeneity between the three periods investigated, we suggest that the phenomenon we present can be explained stress-related effects on decision making rather than by other economic effects, such as the income effect. [ABSTRACT FROM AUTHOR]

Consider the revenue maximization problem of a risk-neutral seller with m heterogeneous items for sale to a single additive buyer, whose values for the items are drawn from known distributions. If the buyer is also risk-neutral, it is known that a simple and natural mechanism, namely the better of selling separately or pricing only the grand bundle, gives a constant-factor approximation to the optimal revenue. In this paper we study revenue maximization without risk-neutral buyers. Specifically, we adopt cumulative prospect theory, a well established generalization of expected utility theory. Our starting observation is that such preferences give rise to a very rich space of mechanisms, allowing the seller to extract arbitrary revenue. Specifically, a seller can construct extreme lotteries that look attractive to a mildly optimistic buyer, but have arbitrarily negative true expectation. Therefore, giving the seller absolute freedom over the design space results in absurd conclusions; competing with the optimal mechanism is hopeless. Instead, in this paper we study four broad classes of mechanisms, each characterized by a distinct use of randomness. Our goal is twofold: to explore the power of randomness when the buyer is not risk-neutral, and to design simple and attitude-agnostic mechanisms—mechanisms that do not depend on details of the buyer's risk attitude—which are good approximations of the optimal in-class mechanism, tailored to a specific risk attitude. Our main result is that the same simple and risk-agnostic mechanism (the better of selling separately or pricing only the grand bundle) is a good approximation to the optimal non-agnostic mechanism within three of the mechanism classes we study. [ABSTRACT FROM AUTHOR]

In many countries, the decline in interest rates has reduced the interest in traditional participating life insurance contracts with investment guarantees and has led to a shift to unit-linked policies without guarantees. We design a novel mixed insurance contract splitting premium payments between a participating and a unit-linked fund. An additional guarantee fee is applied on the unit-linked return in order to increase the investment guarantee of the participating fund. In a utility-based framework, using power utility and prospect theory as preference functions, we show that the mixed product is usually perceived more attractive than a full investment in either the unit-linked or the participating contract. The guarantee fee is beneficial for conservative investors interested in stronger protection against losses. This is also interesting from a marketing perspective: By the increase of the guarantee in the participating product, zero or negative guaranteed rates can be avoided. [ABSTRACT FROM AUTHOR]

Despite their highly idealized nature, certain agent-based models of asset exchange, proposed for the most part by physicists and mathematicians, have been shown to exhibit remarkable agreement with empirical wealth distribution data. While this agre- ement is comforting, there is widespread sentiment that further progress will require a detailed under- standing of the connection between these idealized models and the more realistic microeconomic models of exchange used by economists. In this paper, we examine that connection for a three-parameter asset exchange model, the Affine Wealth Model (AWM), that has demonstrated fraction-of-a-per cent agreement with empirical wealth data. We compare certain properties of this model with those of three great milestones of twentieth century economics, namely (i) Expected Utility Theory, (ii) General Equilibrium Theory and (iii) Prospect Theory. We find that the phenomenology exhibited by the AWM is fundamentally incompatible with Expected Utility Theory and General Equilibrium Theory, but very similar to that exhibited by Prospect Theory. Based on these observations, we argue that AWM transactions are, in a particular sense, an approximation to those described by Prospect Theory, and that Prospect Theory provides the sought-for connection between econophysics and microeconomics, at least for the topic of wealth distribution. This article is part of the theme issue 'Kinetic exchange models of societies and economies'. [ABSTRACT FROM AUTHOR]

Decisions can be risky or riskless, depending on the outcomes of the choice. Expected utility theory describes risky choices as a utility maximization process: we choose the option with the highest subjective value (utility), which we compute considering both the option's value and its associated risk. According to the random utility maximization framework, riskless choices could also be based on a utility measure. Neuronal mechanisms of utility-based choice may thus be common to both risky and riskless choices. This assumption would require the existence of a utility function that accounts for both risky and riskless decisions. Here, we investigated whether the choice behavior of two macaque monkeys in risky and riskless decisions could be described by a common underlying utility function. We found that the utility functions elicited in the two choice scenarios were different from each other, even after taking into account the contribution of subjective probability weighting. Our results suggest that distinct utility representations exist for risky and riskless choices, which could reflect distinct neuronal representations of the utility quantities, or distinct brain mechanisms for risky and riskless choices. The different utility functions should be taken into account in neuronal investigations of utility-based choice. [ABSTRACT FROM AUTHOR]

Original and cumulative prospect theory differ in the composition rule used to combine the probability weighting function and the value function. We test the predictive power of these composition rules by performing a novel out-of-sample prediction test. We apply estimates of prospect theory's weighting and value function obtained from two-outcome cash equivalents, a domain where original and cumulative prospect theory coincide, to three-outcome cash equivalents, a domain where the composition rules of the two theories differ. Although both forms of prospect theory predict three-outcome cash equivalents very well, at the aggregate level, we find small but systematic under-prediction of cash equivalents for cumulative prospect theory and small but systematic over-prediction of cash equivalents for original prospect theory. We also observe substantial heterogeneity across subjects and types of gambles, some of which is accounted for by differences in the curvature and elevation of the weighting function across individuals. We also find differences in prediction related to whether the worst outcome is zero or non-zero. [ABSTRACT FROM AUTHOR]

This work aims to investigate whether individuals, in decision-making in situations at risk, make choices consistent with the prospect theory, seeking to evidence occurrences of certainty, reflection, and isolation effects. For that, a questionnaire was applied, used in the original work by Kahneman and Tversky (1979) and adapted by Faveri et al. (2013), in 73 students of the Accounting Sciences undergraduate course at the Federal University of Juiz de Fora. This questionnaire took place in two moments, the first without knowledge and discussion about the theory of expected utility and, in the second moment, after explaining the concept of expected value. In addition to the analysis of the questions regarding the certainty, reflection, and isolation effects of PD, the originality of the study consists of comparing the results obtained in this research with the results presented in the article by Faveri et al. (2013), which inspired this work. A comparative analysis was also carried out, in a general scope, of the results obtained in the following moment (second application) to the present research, with the results of other selected researches, so that, finally, an analysis was carried out from the perspective of the genre. As the results show, the sample of this work has evidence of the presence of the same biases found by Kahneman and Tversky (1979) and by other empirical studies, strengthening the inferences that behavioral aspects can influence the choices of individuals. [ABSTRACT FROM AUTHOR]

This paper presents a unified approach based on Wasserstein distance to derive concentration bounds for empirical estimates for two broad classes of risk measures defined in the paper. The classes of risk measures introduced include as special cases well known risk measures from the finance literature such as conditional value at risk (CVaR), optimized certainty equivalent risk, spectral risk measures, utility-based shortfall risk, cumulative prospect theory (CPT) value, rank dependent expected utility and distorted risk measures. Two estimation schemes are considered, one for each class of risk measures. One estimation scheme involves applying the risk measure to the empirical distribution function formed from a collection of i.i.d. samples of the random variable (r.v.), while the second scheme involves applying the same procedure to a truncated sample. The bounds provided apply to three popular classes of distributions, namely sub-Gaussian, subexponential and heavy-tailed distributions. The bounds are derived by first relating the estimation error to theWasserstein distance between the true and empirical distributions, and then using recent concentration bounds for the latter. Previous concentration bounds are available only for specific risk measures such as CVaR and CPT-value. The bounds derived in this paper are shown to either match or improve upon previous bounds in cases where they are available. The usefulness of the bounds is illustrated through an algorithm and the corresponding regret bound for a stochastic bandit problem involving a general risk measure from each of the two classes introduced in the paper. [ABSTRACT FROM AUTHOR]

Even if there exists an extensive literature on the modeling of farmers' behavior under risk, actual measurements of the quantitative impact of risk aversion on input use are rare. In this article, we use simulations to quantify the impact of risk aversion on the optimal quantity of input and farmers' welfare when production risk depends on how much of the input is used. The assumptions made on the technology and form of farmers' risk preferences were chosen such that they are fairly representative of crop farming conditions in the USA and Western Europe. In our benchmark scenario featuring a traditional expected utility model, we find that less than 4% of the optimal pesticide expenditure is driven by risk aversion and that risk induces a decrease in welfare that varies from −1.5 to −3.0% for individuals with moderate to normal risk aversion. We find a stronger impact of risk aversion on quantities of input used when farmers' risk preferences are modeled under the cumulative prospect theory framework. When the reference point is set at the median or maximum profit, and for some levels of the parameters that describe behavior toward losses, the quantity of input used that is driven by risk preferences represents up to 19% of the pesticide expenditure. [ABSTRACT FROM AUTHOR]

The definition of best response for a player in the Nash equilibrium is based on maximizing the expected utility given the strategy of the rest of the players in a game. In this work, we consider stochastic games, that is, games with random payoffs, in which a finite number of players engage only once or at most a limited number of times. In such games, players may choose to deviate from maximizing their expected utility. This is because maximizing expected utility strategy does not address the uncertainty in payoffs. We instead define a new notion of a stochastic superiority best response. This notion of best response results in a stochastic superiority equilibrium in which players choose to play the strategy that maximizes the probability of them being rewarded the most in a single round of the game rather than maximizing the expected received reward, subject to the actions of other players. We prove the stochastic superiority equilibrium to exist in all finite games, that is, games with a finite number of players and actions, and numerically compare its performance to Nash equilibrium in finite-time stochastic games. In certain cases, we show the payoff under the stochastic superiority equilibrium is 70% likely to be higher than the payoff under Nash equilibrium. [ABSTRACT FROM AUTHOR]

We consider the long-run outcomes of bargaining games when players obey prospect theory. We extend the evolutionary bargaining model of Young (1993) to a two-stage Nash demand game. Two players simultaneously choose whether to exercise an outside option in the first stage and play the Nash demand game in the second stage, which will be reached only if neither player exercises the outside option. We address the influence on the stochastically stable division of reference-dependent preferences where the reference point is the value of the outside option. We show that the division consistently differs from the Nash bargaining solution under expected utility theory. Inspired by this, we propose a prospect theory Nash bargaining solution , which coincides with the stochastically stable division. [ABSTRACT FROM AUTHOR]

Many studies have spotlighted significant applications of expected utility theory (EUT), cumulative prospect theory (CPT), and mean-variance in assessing risks. We illustrate that these models and their extensions are unable to predict risk behaviors accurately in out-of-sample empirical studies. EUT uses a nonlinear value (utility) function of consequences but is linear in probabilities, which has been criticized as its primary weakness. Although mean-variance is nonlinear in probabilities, it is symmetric, contradicts first-order stochastic dominance, and uses the same standard deviation for both risk aversion and risk proneness. In this paper, we explore a special case of geometric dispersion theory (GDT) that is simultaneously nonlinear in both consequences and probabilities. It complies with first-order stochastic dominance and is asymmetric to represent the mixed risk-averse and risk-prone behaviors of the decision makers. GDT is a triad model that uses expected value, risk-averse dispersion, and risk-prone dispersion. GDT uses only two parameters, z and zX; these constants remain the same regardless of the scale of risk problem. We compare GDT to several other risk dispersion models that are based on EUT and/or mean-variance, and identify verified risk paradoxes that contradict EUT, CPT, and mean-variance but are easily explainable by GDT. We demonstrate that GDT predicts out-of-sample empirical risk behaviors far more accurately than EUT, CPT, mean-variance, and other risk dispersion models. We also discuss the underlying assumptions, meanings, and perspectives of GDT and how it reflects risk relativity and risk triad. This paper covers basic GDT, which is a special case of general GDT of Malakooti [Malakooti (2020) Geometric dispersion theory of decision making under risk: Generalizing EUT, RDEU, & CPT with out-of-sample empirical studies. Working paper, Case Western Reserve University, Cleveland.]. [ABSTRACT FROM AUTHOR]

This study investigates the joint pricing and stocking decisions for a loss‐averse retailer with reference point effect under stochastic demand. By solving an expected utility maximization model developed based on the prospect theory, the optimal pricing and stocking decisions are derived and compared with those of the classical newsvendor. The results show that the optimal decisions significantly depend on the loss aversion coefficient, optimism level, and reference effect strength. Smaller loss aversion coefficient and lower optimism level lead to higher expected utilities. In particular, a loss‐averse retailer with a smaller loss aversion coefficient benefits from a higher reference effect strength and vice versa. [ABSTRACT FROM AUTHOR]

In this paper we examine capital income taxation of a reference dependent sufficiently loss averse investor in a two period portfolio choice model under full loss offset provisions. Capital income taxation with loss offset provisions has been found to stimulate risk taking in expected utility models under certain assumptions about attitudes towards risk but would such effect be found under prospect theory type of preferences? We observe that the impact of capital income taxation depends on investors' reference levels relative to their endowment income and thus we explore capital income taxation for different types of loss averse investors in terms of their ambition. We consider the less ambitious investors to be the ones with relatively low reference levels (they avoid relative losses in both periods) and more ambitious investors to be those with relatively high reference levels. We analyze two types of more ambitious investors: investors with higher time preference (who experience relative losses only in the second period under the bad state of nature) and investors with lower time preference (who experience relative losses only in the first period). We observe that capital income taxation stimulates current consumption in most cases which encourages risk taking, although the final outcome would depend on the investors' degree of risk aversion, the rate of time preference and the tax rate in relation to certain thresholds. Current consumption could be discouraged for some ambitious type of investors that have relatively high second period reference levels but not necessary first period reference levels. In summary, to determine the impact of capital income taxation on the decision variables the reference levels in relation to endowment income play the most significant role. Ignoring reference depended preferences can lead to different conclusions for investors reaction to capital income taxation. We also find certain type of investors whose happiness level increases with capital income taxation under full loss offset provisions. [ABSTRACT FROM AUTHOR]

The most commonly employed paradigms for decision making under risk are expected utility, prospect theory, and regret theory. We examine the simple heuristic of maximizing the probability of being ahead, which in some natural economic situations may be in contradiction to all three of the above fundamental paradigms. We test whether this heuristic, which we call probability dominance (PD), affects decisions under risk. We set up head-to-head situations where all preferences of a given class (expected utility, original or cumulative prospect theory, or regret theory) favor one alternative yet PD favors the other. Our experiments reveal that 49% of subjects' choices are aligned with PD in contradiction to any form of expected utility or prospect theory maximization; 73% are aligned with PD as opposed to preferences under risk aversion and under original and cumulative prospect theory preferences; and 68% to 76% are aligned with PD contradicting preferences under regret theory. We conclude that probability dominance substantially affects choices and should therefore be incorporated into decision-making models. We show that PD has significant economic consequences. The PD heuristic may have evolved through situations of winner-take-all competition. [ABSTRACT FROM AUTHOR]

Many business situations can be called "games" because outcomes depend on multiple decision makers with differing objectives. Yet, in many cases, the payoffs for all combinations of player options are not available, but the ability to experiment off-line is available. For example, war-gaming exercises, test marketing, cyber-range activities, and many types of simulations can all be viewed as off-line gaming-related experimentation. We address the decision problem of planning and analyzing off-line experimentation for games with an initial procedure seeking to minimize the errors in payoff estimates. Then, we provide a sequential algorithm with reduced selections from option combinations that are irrelevant to evaluating candidate Nash, correlated, cumulative prospect theory or other equilibria. We also provide an efficient formula to estimate the chance that given Nash equilibria exists, provide convergence guarantees relating to general equilibria, and provide a stopping criterion called the estimated expected value of perfect off-line information (EEVPOI). The EEVPOI is based on bounded gains in expected utility from further off-line experimentation. An example of using a simulation model to illustrate all the proposed methods is provided based on a cyber security capture-the-flag game. The example demonstrates that the proposed methods enable substantial reductions in both the number of test runs (half) compared with a full factorial and the computational time for the stopping criterion. [ABSTRACT FROM AUTHOR]

The majority consensus in the empirical literature is that probability weighting functions are typically inverse-S shaped, that is, people tend to overweight small and underweight large probabilities. A separate stream of literature has reported event-splitting effects (also called violations of coalescing) and shown that they can explain violations of expected utility. This leads to the questions whether (1) the observed shape of weighting functions is a mere consequence of the coalesced presentation and, more generally, whether (2) preference elicitation should rely on presenting lotteries in a canonical split form instead of the commonly used coalesced form. We analyze data from a binary choice experiment where all lottery pairs are presented in both split and coalesced forms. Our results show that the presentation in a split form leads to a better fit of expected utility theory and to probability weighting functions that are closer to linear. We thus provide some evidence that the extent of probability weighting is not an ingrained feature, but rather a result of processing difficulties. [ABSTRACT FROM AUTHOR]

Stated choice analysis has been extensively applied to understand choice behavior with travel time variability. However, under a risk-neutral and belief-neutral assumption, the conventional approach to travel time variability has a number of behavioral limitations. In this review paper, we illustrate the violation of linear utility maximization under the traditional risk-neutral assumption and the violation of linear probability weighting under the belief-neutral assumption. This paper also reviews recent stated preference studies based on behaviorally superior theories (Expected Utility Theories, Rank-Dependent Utility Theory, Cumulative Prospect Theory) that have accommodated the role of risk attitude and/or belief in understanding risky travel choice behavior, including their behavioral contributions and major advancements over previous studies. We also highlight several common errors in the majority of the existing studies including the interpretation of risk attitude, the specification of nonlinear utility and the t-test for nonlinear probability weighting, and suggest ways to avoid these problems. Several avenues for future research are set out. [ABSTRACT FROM AUTHOR]

The expected utility theory axioms have been studied experimentally. Three of the experiments are a repetition of an earlier test in slightly changed circumstances, while the other two are original. The participants were incentivised with rewards, which did not happen in the replicated tests. The results confirmed the degeneration of the expected utility theory as a scientific research program. The evidence that resulted from the tests supported the hypothesis on the cumulative prospect theory predicting facts not forecasted by the EUT. [ABSTRACT FROM AUTHOR]

According to behavioural finance, economic agents display cognitive bias, heuristics and emotional factors that generate preferences which systematically violate the rationality assumptions of the normative model of classical decision theory. Rather than maximizing the expected utility, representing the optimal choice, they attempt to accept a satisfactory solution. Morton and Fasolo (J Oper Res Soc 60:268–275, 2009) outlined some behavioural findings relevant to the practice of multicriteria approach. In this paper, we propose a multicriteria model for analysing some experiments proposed by Kahneman and Tversky (Econometrica 47:263–29 l, 1979). Our aim is to verify whether a multicriteria tool reduces or minimizes cognitive biases. We focus on ELECTRE due to its main features: it accepts the violation of some mathematical axioms. By a simulation study, we represent a set of prospects by means of decision matrices: the prospects are considered as alternatives, the events as criteria, the probabilities of events as the weights assigned to criteria. Then, we apply ELECTRE to verify whether the preference ranking among the alternatives confirms the results obtained by Kahneman–Tversky, that is, whether it is able to describe the emotional behaviours of economic agents. [ABSTRACT FROM AUTHOR]

This paper develops normative approaches for measuring individual-level income insecurity. Using concepts derived from Expected Utility Theory and Prospect Theory, we build a suite of measures designed to capture various facets of psychologically distressing income risk. We present an application for the US and Germany from 1993–2013, employing conditionally heteroskedastic fixed-effects models to generate predictive densities for future incomes. Our results reveal much higher levels of income risk in the US relative to Germany, which can be mostly attributed to a higher level of autonomous, time-invariant volatility. State-by-state variations in liberal/conservative political administrations partially explain our results, and we find some evidence that trade exposure is a contributing factor in the US. [ABSTRACT FROM AUTHOR]

A number of agricultural and food policy instruments are predicated on the idea that producers dislike output price risk. We test experimentally some theoretical predictions about the behavior of producers in the face of output price risk, namely Sandmo's (1971) prediction that price risk at the extensive margin causes risk‐averse producers to decrease how much they produce and Batra and Ullah's (1974) prediction that price risk at the intensive margin causes producers whose preferences exhibit decreasing absolute risk aversion to further decrease how much they produce. We do so in labs with US college students as well as in the field with Peruvian farmers. First, as regards price risk at the extensive margin, we find no support for Sandmo's prediction. Second, consistent with Batra and Ullah's prediction, we find that output decreases in response to price risk at the intensive margin when imposing a linear relationship between output and price risk. When relaxing the assumption of linearity between output and price risk, however, we find a nonmonotonic relationship between output and price risk. Taken together, these results are broadly inconsistent with expected utility theory. Alternative models of behavior in the face of risk, such as prospect theory, may explain the behavior we observe. [ABSTRACT FROM AUTHOR]

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. In this article, 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 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 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. Furthermore, we put forward asymmetric weighted moving average 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 with that obtained by prospect theory. The simulation results reveal that prospect theory quantifies trustworthiness of the aggregate data better than expected utility theory. [ABSTRACT FROM AUTHOR]