Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/179243
Authors: 
Zhao, Feng
Gao, Jianwei
Gu, Yundong
Year of Publication: 
2018
Series/Report no.: 
Economics Discussion Papers 2018-46
Abstract: 
Almost stochastic dominance is a relaxation of stochastic dominance, which allows small violations of stochastic dominance rules to avoid situations where most decision makers prefer one alternative to another but stochastic dominance cannot rank them. The authors first discuss the relations between almost first-degree stochastic dominance (AFSD) and the second-degree stochastic dominance (SSD), and demonstrate that the AFSD criterion is helpful to narrow down the SSD efficient set. Since the existing AFSD criterion is not convenient to rank transformations of random variables due to its relying heavily on cumulative distribution functions, the authors propose the AFSD criterion for transformations of random variables by means of transformation functions and the probability function of the original random variable. Moreover, they employ this method to analyze the transformations resulting from insurance and option strategy.
Subjects: 
stochastic dominance
almost stochastic dominance
transformation
utility theory
JEL: 
C51
D81
Creative Commons License: 
http://creativecommons.org/licenses/by/4.0/
Document Type: 
Working Paper
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