An optimal double stopping rule for a buying-selling problem

    Research output: Contribution to journalArticleResearchpeer-review

    Abstract

    We consider a buying-selling problem with a finite time horizon when two stops of a sequence of dependent observations can be made. The aim is to find an optimal sequential procedure which maximizes the total expected revenue. In this paper, we obtain an optimal double stopping rule and apply it for a geometric random walk and an autoregressive sequence.

    LanguageEnglish
    JournalMethodology and Computing in Applied Probability
    Early online date3 Nov 2018
    DOIs
    Publication statusE-pub ahead of print - 3 Nov 2018

    Fingerprint

    Stopping Rule
    Dependent Observations
    Sequential Procedure
    Horizon
    Random walk
    Maximise

    Keywords

    • Autoregressive sequence
    • Buying-selling problem
    • Geometric random walk
    • Optimal stopping rules
    • Sequential decision analysis

    Cite this

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    abstract = "We consider a buying-selling problem with a finite time horizon when two stops of a sequence of dependent observations can be made. The aim is to find an optimal sequential procedure which maximizes the total expected revenue. In this paper, we obtain an optimal double stopping rule and apply it for a geometric random walk and an autoregressive sequence.",
    keywords = "Autoregressive sequence, Buying-selling problem, Geometric random walk, Optimal stopping rules, Sequential decision analysis",
    author = "Sofronov, {Georgy Yu}",
    year = "2018",
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    doi = "10.1007/s11009-018-9684-6",
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    An optimal double stopping rule for a buying-selling problem. / Sofronov, Georgy Yu.

    In: Methodology and Computing in Applied Probability, 03.11.2018.

    Research output: Contribution to journalArticleResearchpeer-review

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