scholarly journals Salience and Skewness Preferences

2019 ◽  
Vol 18 (5) ◽  
pp. 2057-2107 ◽  
Author(s):  
Markus Dertwinkel-Kalt ◽  
Mats Köster

Abstract Whether people seek or avoid risks on gambling, insurance, asset, or labor markets crucially depends on the skewness of the underlying probability distribution. In fact, people typically seek positively skewed risks and avoid negatively skewed risks. We show that salience theory of choice under risk can explain this preference for positive skewness, because unlikely, but outstanding payoffs attract attention. In contrast to alternative models, however, salience theory predicts that choices under risk not only depend on the absolute skewness of the available options, but also on how skewed these options appear to be relative to each other. We exploit this fact to derive novel, experimentally testable predictions that are unique to the salience model and that we find support for in two laboratory experiments. We thereby argue that skewness preferences—typically attributed to cumulative prospect theory—are more naturally accommodated by salience theory.

2013 ◽  
Vol 2 (2) ◽  
pp. 97-108
Author(s):  
David Peel

Given that the expected return and variance of return of two gambles are equal  the hypothesis that the gamble with the greater  positive skewness of return will be chosen by an expected utility maximiser is appealing. However the hypothesis is  not, in general, correct. Brockett and Garven (1998) and Brocket and Kahane (1992) demonstrate this both theoretically and by constructing counter examples.A particularly revealing example is the following one constructed by Brockett and Kahane.  Gamble A has the two outcomes 2.45 and 7.49 with probabilities 0.5141 and 0.4859 respectively. Gamble B has the three outcomes 0, 4.947 and 10 with probabilities 0.12096, 0.750085 and 0.128955 respectively. Even though gamble A exhibits  lower expected return,  a higher variance and lower  positive skewness than gamble B it is preferred to gamble B by an expected utility maximiser on the basis of any standard utility function  such as power, log or exponential.  Consequently in this  example of theirs the expected utility maximiser exhibits an aversion to higher expected return and higher skewness and a preference for higher variance. As noted by Brockett and Kahane these results cannot be dismissed as decision makers “trading” variance for mean or skewness or having a strange idiosyncratic utility function.


Author(s):  
N. N. Trakakis

First, the nature of ‘anti-theodicy’ is outlined, and some indication is provided as to how this position differs from both theodicy and skeptical theism, and how the anti-theodicy view can be supported on the basis of moral and methodological considerations. Secondly, a possible metaphysical basis for anti-theodicy is sought, and this is achieved by abandoning anthropomorphic conceptions of God in favour of alternative models of divinity that might make possible new and more fruitful perspectives on the problem of evil. The alternative model advanced here for special attention is the Absolute Idealism of F. H. Bradley. The chapter concludes by showing how the problem of evil can be answered from a Bradleian perspective.


2021 ◽  
pp. 1-13
Author(s):  
Ning Tao ◽  
Duan Xiaodong ◽  
An Lu ◽  
Gou Tao

A disruption management method based on cumulative prospect theory is proposed for the urgent with deteriorating effect arrival in flexible job shop scheduling problem (FJSP). First, the mathematical model of problem is established with minimizing the completion time of urgent order, minimizing the total process time of the system and minimizing the total cost as the target. Then, the cumulative prospect theory equation of the urgent arrival in job shop scheduling process is induced designed. Based on the selected model, an optimized multi-phase quantum particle swarm algorithm (MQPSO) is proposed for selecting processing route. Finally, using Solomon example simulation and company Z riveting shop example as the study object, the performance of the proposed method is analyzed. It is compared with the current common rescheduling methods, and the results verify that the method proposed in this paper not only meets the goal of the optimized objects, but improves the practical requirements for the stability of production and processing system during urgent arrival. Lastly, the optimized multiphase quantum particle swarm algorithm is used to solve disruption management of urgent arrival problem. Through instance analysis and comparison, the effectiveness and efficiency of urgent arrival disruption management method with deteriorating effect are verified.


2020 ◽  
Vol 12 (6) ◽  
pp. 064101
Author(s):  
Jicheng Liu ◽  
Zhenzhen Wang ◽  
Yu Yin ◽  
Yinghuan Li ◽  
Yunyuan Lu

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