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A Bayesian decision model based on expected utility and uncertainty risk
- Authors
- Park, Changsoon; Ahn, Suneung; Lee, Sangwon
- Issue Date
- Sep-2014
- Publisher
- Elsevier BV
- Keywords
- Decision analysis; Expected utility; Uncertainty; Prior distribution
- Citation
- Applied Mathematics and Computation, v.242, pp 643 - 648
- Pages
- 6
- Indexed
- SCIE
SCOPUS
- Journal Title
- Applied Mathematics and Computation
- Volume
- 242
- Start Page
- 643
- End Page
- 648
- ISSN
- 0096-3003
1873-5649
- Abstract
- Risk is caused by the uncertainty of state of nature and a decision maker's selection, and the result may appear to be an unfavorable outcome. Therefore, a decision maker wants to maximize an expected return with minimal risk exposures. In this paper, we propose an expected utility and uncertainty risk (EU-UR) model based on the reference prior, which extends the classical decision model under uncertainty. The EU-UR model is made by making a compromise between measures of expected utility and uncertainty. The model is empirically validated by applying to the Levy's case and the Allais paradox. (C) 2014 Elsevier Inc. All rights reserved.
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