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Moment-based minimax stopping functions for sequences of random variables

Author

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  • Boshuizen, Frans A.
  • Hill, T. P.

Abstract

Minimax-optimal stopping times and minimax (worst-case) distributions are found for the problem of stopping a sequence of uniformly bounded independent random variables, when only the means and/or variances are known, in contrast to the classical setting where the complete joint distributions of the random variables are known. Results are obtained for both the independent and i.i.d. cases, with applications given to the problem of order section in optimal stopping.

Suggested Citation

  • Boshuizen, Frans A. & Hill, T. P., 1992. "Moment-based minimax stopping functions for sequences of random variables," Stochastic Processes and their Applications, Elsevier, vol. 43(2), pages 303-316, December.
    • Handle: RePEc:eee:spapps:v:43:y:1992:i:2:p:303-316
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    Cited by:

    1. Alexander Alvarez & Sebastian Ferrando, 2014. "Trajectory Based Models, Arbitrage and Continuity," Papers 1403.5685, arXiv.org, revised Jan 2015.
    2. Alexander Alvarez & Sebastian E. Ferrando, 2016. "Trajectory-Based Models, Arbitrage And Continuity," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 1-34, May.
    3. Pieter Kleer & Johan van Leeuwaarden, 2022. "Optimal Stopping Theory for a Distributionally Robust Seller," Papers 2206.02477, arXiv.org, revised Jun 2022.

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