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    Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/104866


    Title: Generalized almost stochastic dominance
    Authors: 黃瑞卿;Tsetlin, Ilia;Winkler, Robert L.;Huang, Rachel J.;Tzeng, Larry Y.
    Contributors: 管理學院財務金融學系
    Keywords: Analysis;Decision analysis;Decision theory;distribution comparisons;Dominance;Empirical analysis;METHODS;Operations research;Preferences;probability;risk;stochastic dominance;Stochastic models;utility;Utility theory
    Date: 2015-01-01
    Issue Date: 2026-04-23 12:00:08 (UTC+8)
    Publisher: INFORMS Institute for Operations Research and the Management Sciences;Linthicum: INFORMS
    Abstract: 摘要: Almost stochastic dominance 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. While the idea behind almost stochastic dominance is quite promising, it has not caught on in practice. Implementation issues and inconsistencies between integral conditions and their associated utility classes contribute to this situation. We develop generalized almost second-degree stochastic dominance and almost second-degree risk in terms of the appropriate utility classes and their corresponding integral conditions, and extend these concepts to higher degrees. We address implementation issues and show that generalized almost stochastic dominance inherits the appealing properties of stochastic dominance. Finally, we define convex generalized almost stochastic dominance to deal with risk-prone preferences. Generalized almost stochastic dominance could be useful in decision analysis, empirical research (e.g., in finance), and theoretical analyses of applied situations.
    出版者: Linthicum: INFORMS
    出版日期: 2015-03-01
    出處: Operations research, 2015-03, Vol.63 (2), p.363-377
    資源來源: JSTOR Arts and Sciences IV
    版權: 2015 INFORMS
    版權: COPYRIGHT 2015 Institute for Operations Research and the Management Sciences
    版權: Copyright Institute for Operations Research and the Management Sciences Mar/Apr 2015
    識別號: ISSN: 0030-364X
    識別號: EISSN: 1526-5463
    識別號: DOI: 10.1287/opre.2014.1340
    Appears in Collections:[Department of Finance] journal & Dissertation

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