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Prospect theory for continuous distributions


Rieger, Marc Oliver; Wang, Mei (2008). Prospect theory for continuous distributions. Journal of Risk and Uncertainty, 36(1):83-102.

Abstract

We extend the original form of prospect theory by Kahneman and Tversky from finite lotteries to arbitrary probability distributions, using an approximation method based on weak-⋆ convergence. The resulting formula is computationally easier than the corresponding formula for cumulative prospect theory and makes it possible to use prospect theory in future applications in economics and finance. Moreover, we suggest a method how to incorporate a crucial step of the “editing phase” into prospect theory and to remove in this way the discontinuity of the original model.

We extend the original form of prospect theory by Kahneman and Tversky from finite lotteries to arbitrary probability distributions, using an approximation method based on weak-⋆ convergence. The resulting formula is computationally easier than the corresponding formula for cumulative prospect theory and makes it possible to use prospect theory in future applications in economics and finance. Moreover, we suggest a method how to incorporate a crucial step of the “editing phase” into prospect theory and to remove in this way the discontinuity of the original model.

Citations

6 citations in Web of Science®
11 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, further contribution
Communities & Collections:03 Faculty of Economics > Department of Banking and Finance
Dewey Decimal Classification:330 Economics
Uncontrolled Keywords:Prospect theory - Cumulative prospect theory - Continuity - Probability weighting - First-order stochastic dominance
Language:English
Date:February 2008
Deposited On:09 Dec 2008 10:05
Last Modified:05 Apr 2016 12:29
Publisher:Springer
ISSN:0895-5646
Additional Information:The original publication is available at www.springerlink.com
Publisher DOI:10.1007/s11166-007-9029-2
Permanent URL: http://doi.org/10.5167/uzh-4268

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