scholarly journals An empirical test of gain-loss separability in prospect theory

2004 ◽  
Author(s):  
George Wu ◽  
Alex B. Markle
Keyword(s):  
Prospect Theory ◽  
Empirical Test ◽  
Gain Loss

scholarly journals An Empirical Test of Gain-Loss Separability in Prospect Theory

2008 ◽  
Vol 54 (7) ◽  
pp. 1322-1335 ◽  
Author(s):  
George Wu ◽  
Alex B. Markle
Keyword(s):  
Prospect Theory ◽  
Empirical Test ◽  
Gain Loss

Prospect Theory and Stock Returns: An Empirical Test

2016 ◽  
Vol 29 (11) ◽  
pp. 3068-3107 ◽  
Author(s):  
Nicholas Barberis ◽  
Abhiroop Mukherjee ◽  
Baolian Wang
Keyword(s):  
Stock Returns ◽  
Prospect Theory ◽  
Empirical Test

scholarly journals An Experimental Comparison of Risky and Riskless Choice—Limitations of Prospect Theory and Expected Utility Theory

2019 ◽  
Vol 11 (3) ◽  
pp. 34-67 ◽  
Author(s):  
Hui-Kuan Chung ◽  
Paul Glimcher ◽  
Agnieszka Tymula
Keyword(s):  
Prospect Theory ◽  
Empirical Evidence ◽  
Expected Utility ◽  
Utility Theory ◽  
Expected Utility Theory ◽  
Experimental Comparison ◽  
Reference Dependence ◽  
Empirical Results ◽  
Incentive Compatible ◽  
Gain Loss

Prospect theory, used descriptively for decisions under both risk and certainty, presumes concave utility over gains and convex utility over losses; a pattern widely seen in lottery tasks. Although such discontinuous gain-loss reference-dependence is also used to model riskless choices, only limited empirical evidence supports this use. In incentive-compatible experiments, we find that gain-loss reflection effects are not observed under riskless choice as predicted by prospect theory, even while in the same subjects gain-loss reflection effects are observed under risk. Our empirical results challenge the application of choice models across both risky and riskless domains. (JEL C91, D12, D81)

scholarly journals Primate anterior insular cortex represents economic decision variables postulated by Prospect theory

2020 ◽  
Author(s):  
You-Ping Yang ◽  
Xinjian Li ◽  
Veit Stuphorn
Keyword(s):  
Prospect Theory ◽  
Reference Point ◽  
Contextual Information ◽  
Insular Cortex ◽  
Risk Attitude ◽  
Risky Decision ◽  
Anterior Insular Cortex ◽  
Decision Variables ◽  
Gain Loss

AbstractIn humans, risk attitude is highly context-dependent, varying with wealth levels or for different potential outcomes, such as gains or losses. These behavioral effects are well described by Prospect Theory, with the key assumption that humans represent the value of each available option asymmetrically as gain or loss relative to a reference point. However, it remains unknown how these computations are implemented at the neuronal level. Using a new token gambling task, we found that macaques, like humans, change their risk attitude across wealth levels and gain/loss contexts. Neurons in their anterior insular cortex (AIC) encode the ‘reference point’ (i.e. the current wealth level of the monkey) and the ‘asymmetric value function’ (i.e. option value signals are more sensitive to change in the loss than in the gain context) as postulated by Prospect Theory. In addition, changes in the activity of a subgroup of AIC neurons are correlated with the inter-trial fluctuations in choice and risk attitude. Taken together, we find that the role of primate AIC in risky decision-making is to monitor contextual information used to guide the animal’s willingness to accept risk.

Academic Decision Making and Prospect Theory

2011 ◽  
Vol 109 (1) ◽  
pp. 289-300
Author(s):  
Robert R. Mowrer ◽  
William B. Davidson
Keyword(s):  
College Students ◽  
Decision Making ◽  
Prospect Theory ◽  
High Probability ◽  
Dependent Measure ◽  
Risk Seeking ◽  
Gain Loss ◽  
Academic Decision Making ◽  
Fourfold Pattern ◽  
Loss Effect

Two studies are reported that investigate the applicability of prospect theory to college students' academic decision making. Exp. 1 failed to provide support for the risk-seeking portion of the fourfold pattern predicted by prospect theory but did find the greater weighting of losses over gains. Using a more sensitive dependent measure, in Exp. 2 the results of the first experiment were replicated in terms of the gain-loss effect and also found some support for the fourfold pattern in the interaction between probabilities and gain versus loss. The greatest risk-seeking was found in the high probability loss condition.

Reference-Dependent Risk Attitudes

2007 ◽  
Vol 97 (4) ◽  
pp. 1047-1073 ◽  
Author(s):  
Botond Kőszegi ◽  
Matthew Rabin
Keyword(s):  
Risk Aversion ◽  
Prospect Theory ◽  
Large Scale ◽  
Risk Attitudes ◽  
Additional Risk ◽  
First Order ◽  
Prior Expectation ◽  
Probabilistic Beliefs ◽  
Gain Loss ◽  
Delayed Consequences

We use Kőszegi and Rabin's (2006) model of reference-dependent utility, and an extension of it that applies to decisions with delayed consequences, to study preferences over monetary risk. Because our theory equates the reference point with recent probabilistic beliefs about outcomes, it predicts specific ways in which the environment influences attitudes toward modest-scale risk. It replicates “classical” prospect theory—including the prediction of distaste for insuring losses—when exposure to risk is a surprise, but implies first-order risk aversion when a risk, and the possibility of insuring it, are anticipated. A prior expectation to take on risk decreases aversion to both the anticipated and additional risk. For large-scale risk, the model allows for standard “consumption utility” to dominate reference-dependent “gain-loss utility,” generating nearly identical risk aversion across situations. (JEL D81)

scholarly journals You cannot accurately estimate an individual’s loss aversion using an accept-reject task

2020 ◽  
Author(s):  
Lukasz Walasek ◽  
Neil Stewart
Keyword(s):  
Prospect Theory ◽  
Loss Aversion ◽  
Model Parameters ◽  
Probability Weighting ◽  
Value Functions ◽  
Trade Off ◽  
Simple Version ◽  
The Poor ◽  
Gain Loss ◽  
Linear Probability

Prospect theory's loss aversion is often measured in the accept-reject task, in which participants accept or reject the chance of playing a series of gambles. The gambles are two-branch 50/50 gambles with varying gain and loss amounts (e.g., 50% chance of winning $20 and a 50% chance of losing $10). Prospect theory quantifies loss aversion by scaling losses up by a parameter λ. Here we show that λ suffers from extremely poor parameter recoverability in the accept-reject task. λ cannot be reliably estimated even for a simple version of prospect theory with linear probability weighting and value functions. λ cannot be reliably estimated even in impractically large experiments with participants subject to thousands of choices. The poor recoverability is driven by a trade-off between λ and the other model parameters. However, a measure derived from these parameters is extremely well recovered—and corresponds to estimating the area of gain-loss space in which people accept gambles. This area is equivalent to the number of gambles accepted in a given choice set. That is, simply counting accept decisions is extremely reliably recovered—but using prospect theory to make further use of exactly which gambles were accepted and which were rejected does not work.

Sign in / Sign up

Export Citation Format

Share Document