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Probabilistic extention of the cumulative prospect theory


  • Ilya Zutler

    () (National Research University Higher School of Economics. Faculty of Economics, Department of Higher Mathematics)


A number of experiments indicate probabilistic preferences in cases where no one alternative is absolutely optimal. The task of predicting the choice of one of the alternatives among multiple alternatives is then practically important and not trivial. It can occur in situations of choice under risk when no one lottery stochastically dominates others. For risky lotteries there are several complicated models of probabilistic binary preference. For the first time, we herein propose the probabilistic extension of the cumulative prospect theory (CPT). The presented visual graphic justification of this model is intuitively clear and does not use sophisticated cumulative summing or a Choquet integral. Here we propose a model of selecting from a set of alternatives by continuous Markov random walks. It makes predicting the results of a choice easy because it fully uses dates received by probabilistic extension of ÑPT. The proposed methods are quite simple and do not require a large amount of data for practical use

Suggested Citation

  • Ilya Zutler, 2013. "Probabilistic extention of the cumulative prospect theory," HSE Working papers WP BRP 33/EC/2013, National Research University Higher School of Economics.
  • Handle: RePEc:hig:wpaper:33/ec/2013

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    cumulative prospect theory; probabilistic choice; continues Markov process.;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

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