Browsing by Subject "Prospect theory"

Now showing 1 - 3 of 3

Open Access
Endogenous reference points in bargaining
(Springer Verlag, 2018) Karagözoğlu, Emin; Keskin, K.
We allow the reference point in (cooperative) bargaining problems with a reference point to be endogenously determined. Two loss averse agents simultaneously and strategically choose their reference points, taking into consideration that with a certain probability they will not be able to reach an agreement and will receive their disagreement point outcomes, whereas with the remaining probability an arbitrator will distribute the resource by using (an extended) Gupta-Livne bargaining solution (Gupta and Livne in Manag Sci 34:1303-1314, 1988). The model delivers intuitive equilibrium comparative statics on the breakdown probability, the loss aversion coefficients, and the disagreement point outcomes.
Open Access
First price auctions under prospect theory with linear probability weighting
(2011) Keskin, Kerim
Overbidding in first-price sealed-bid auctions is a well-known result in the auction theory literature. For the possible reasons behind this phenomenon, economists provided many explanations; such as risk aversion, regret theory, and subjective probability weighting. However, for subjective probability weighting to explain overbidding, the probability weighting function (PWF) is needed to be underweighting all probabilities. Such a function is not in accord with PWFs in the prospect theory literature as it suggests a specific function which satisfies certain properties. In this paper we investigate, to what extent prospect theory is able to explain overbidding by using a linear PWF satisfying all of the axiomatic properties (Currim and Sarin, 1989). Moreover, we introduce a non-zero reference point, fully utilizing prospect theory. Our results show that, subjective probability weighting alone is unable to explain overbidding. However, with the non-zero reference point assumption, we obtain partial overbidding.
Open Access
On the optimality of likelihood ratio test for prospect theory-based binary hypothesis testing
(Institute of Electrical and Electronics Engineers, 2018) Gezici, Sinan; Varshney, P. K.
In this letter, the optimality of the likelihood ratio test (LRT) is investigated for binary hypothesis testing problems in the presence of a behavioral decision-maker. By utilizing prospect theory, a behavioral decision-maker is modeled to cognitively distort probabilities and costs based on some weight and value functions, respectively. It is proved that the LRT may or may not be an optimal decision rule for prospect theory-based binary hypothesis testing, and conditions are derived to specify different scenarios. In addition, it is shown that when the LRT is an optimal decision rule, it corresponds to a randomized decision rule in some cases; i.e., nonrandomized LRTs may not be optimal. This is unlike Bayesian binary hypothesis testing, in which the optimal decision rule can always be expressed in the form of a nonrandomized LRT. Finally, it is proved that the optimal decision rule for prospect theory-based binary hypothesis testing can always be represented by a decision rule that randomizes at most two LRTs. Two examples are presented to corroborate the theoretical results.