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Optimal stopping under probability distortion

  • Zuo Quan Xu
  • Xun Yu Zhou
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    We formulate an optimal stopping problem for a geometric Brownian motion where the probability scale is distorted by a general nonlinear function. The problem is inherently time inconsistent due to the Choquet integration involved. We develop a new approach, based on a reformulation of the problem where one optimally chooses the probability distribution or quantile function of the stopped state. An optimal stopping time can then be recovered from the obtained distribution/quantile function, either in a straightforward way for several important cases or in general via the Skorokhod embedding. This approach enables us to solve the problem in a fairly general manner with different shapes of the payoff and probability distortion functions. We also discuss economical interpretations of the results. In particular, we justify several liquidation strategies widely adopted in stock trading, including those of "buy and hold", "cut loss or take profit", "cut loss and let profit run" and "sell on a percentage of historical high".

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    File URL: http://arxiv.org/pdf/1103.1755
    File Function: Latest version
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    Paper provided by arXiv.org in its series Papers with number 1103.1755.

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    Date of creation: Mar 2011
    Date of revision: Feb 2013
    Publication status: Published in Annals of Applied Probability 2013, Vol. 23, No. 1, 251-282
    Handle: RePEc:arx:papers:1103.1755
    Contact details of provider: Web page: http://arxiv.org/

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