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Partially observed control of a Markov jump process with counting observations: equivalence with the separated problem

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  • Ceci, Claudia
  • Gerardi, Anna

Abstract

This paper concerns a partially observable finite horizon control problem for -valued pure Markov jump process using the information given by the point process which counts the total number of jumps. Equivalence between the partially observable control problem and the separated control problem is discussed.

Suggested Citation

  • Ceci, Claudia & Gerardi, Anna, 1998. "Partially observed control of a Markov jump process with counting observations: equivalence with the separated problem," Stochastic Processes and their Applications, Elsevier, vol. 78(2), pages 245-260, November.
    • Handle: RePEc:eee:spapps:v:78:y:1998:i:2:p:245-260
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    References listed on IDEAS

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    1. Arjas, Elja & Haara, Pentti & Norros, Ikka, 1992. "Filtering the histories of a partially observed marked point process," Stochastic Processes and their Applications, Elsevier, vol. 40(2), pages 225-250, March.
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    Cited by:

    1. Suhan Altay & Katia Colaneri & Zehra Eksi, 2017. "Portfolio optimization for a large investor controlling market sentiment under partial information," Papers 1706.03567, arXiv.org.
    2. Giorgia Callegaro & Claudia Ceci & Giorgio Ferrari, 2019. "Optimal Reduction of Public Debt under Partial Observation of the Economic Growth," Papers 1901.08356, arXiv.org, revised Jan 2019.
    3. Bayraktar, Erhan & Ludkovski, Michael, 2009. "Sequential tracking of a hidden Markov chain using point process observations," Stochastic Processes and their Applications, Elsevier, vol. 119(6), pages 1792-1822, June.
    4. Giorgia Callegaro & Claudia Ceci & Giorgio Ferrari, 2020. "Optimal reduction of public debt under partial observation of the economic growth," Finance and Stochastics, Springer, vol. 24(4), pages 1083-1132, October.
    5. Callegaro, Giorgia & Ceci, Claudia & Ferrari, Giorgio, 2019. "Optimal Reduction of Public Debt under Partial Observation of the Economic Growth," Center for Mathematical Economics Working Papers 608, Center for Mathematical Economics, Bielefeld University.

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