A new strategy for Robbins' problem of optimal stopping

Martin Meier, Leopold Soegner

    Research output: Contribution to journalArticle

    Abstract

    In this paper we study the expected rank problem under full information. Our approach uses the planar Poisson approach from Gnedin (2007) to derive the expected rank of a stopping rule that is one of the simplest nontrivial examples combining rank dependent rules with threshold rules. This rule attains an expected rank lower than the best upper bounds obtained in the literature so far, in particular, we obtain an expected rank of 2.326 14.

    Original languageEnglish (US)
    Pages (from-to)331-336
    Number of pages6
    JournalJournal of Applied Probability
    Volume54
    Issue number1
    DOIs
    StatePublished - Mar 1 2017

    Fingerprint

    Optimal Stopping
    Stopping Rule
    Siméon Denis Poisson
    Strategy
    Optimal stopping
    Upper bound
    Dependent

    Keywords

    • Optimal stopping
    • Robbins' problem

    ASJC Scopus subject areas

    • Statistics and Probability
    • Mathematics(all)
    • Statistics, Probability and Uncertainty

    Cite this

    A new strategy for Robbins' problem of optimal stopping. / Meier, Martin; Soegner, Leopold.

    In: Journal of Applied Probability, Vol. 54, No. 1, 01.03.2017, p. 331-336.

    Research output: Contribution to journalArticle

    Meier, Martin ; Soegner, Leopold. / A new strategy for Robbins' problem of optimal stopping. In: Journal of Applied Probability. 2017 ; Vol. 54, No. 1. pp. 331-336.
    @article{7b788c22c0f84659b3b9eb33ee218884,
    title = "A new strategy for Robbins' problem of optimal stopping",
    abstract = "In this paper we study the expected rank problem under full information. Our approach uses the planar Poisson approach from Gnedin (2007) to derive the expected rank of a stopping rule that is one of the simplest nontrivial examples combining rank dependent rules with threshold rules. This rule attains an expected rank lower than the best upper bounds obtained in the literature so far, in particular, we obtain an expected rank of 2.326 14.",
    keywords = "Optimal stopping, Robbins' problem",
    author = "Martin Meier and Leopold Soegner",
    year = "2017",
    month = "3",
    day = "1",
    doi = "10.1017/jpr.2016.103",
    language = "English (US)",
    volume = "54",
    pages = "331--336",
    journal = "Journal of Applied Probability",
    issn = "0021-9002",
    publisher = "University of Sheffield",
    number = "1",

    }

    TY - JOUR

    T1 - A new strategy for Robbins' problem of optimal stopping

    AU - Meier, Martin

    AU - Soegner, Leopold

    PY - 2017/3/1

    Y1 - 2017/3/1

    N2 - In this paper we study the expected rank problem under full information. Our approach uses the planar Poisson approach from Gnedin (2007) to derive the expected rank of a stopping rule that is one of the simplest nontrivial examples combining rank dependent rules with threshold rules. This rule attains an expected rank lower than the best upper bounds obtained in the literature so far, in particular, we obtain an expected rank of 2.326 14.

    AB - In this paper we study the expected rank problem under full information. Our approach uses the planar Poisson approach from Gnedin (2007) to derive the expected rank of a stopping rule that is one of the simplest nontrivial examples combining rank dependent rules with threshold rules. This rule attains an expected rank lower than the best upper bounds obtained in the literature so far, in particular, we obtain an expected rank of 2.326 14.

    KW - Optimal stopping

    KW - Robbins' problem

    UR - http://www.scopus.com/inward/record.url?scp=85017120880&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=85017120880&partnerID=8YFLogxK

    U2 - 10.1017/jpr.2016.103

    DO - 10.1017/jpr.2016.103

    M3 - Article

    VL - 54

    SP - 331

    EP - 336

    JO - Journal of Applied Probability

    JF - Journal of Applied Probability

    SN - 0021-9002

    IS - 1

    ER -