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On optimal periodic dividend strategies for Lévy risk processes

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  • Noba, Kei
  • Pérez, José-Luis
  • Yamazaki, Kazutoshi
  • Yano, Kouji

Abstract

In this paper, we revisit the optimal periodic dividend problem, in which dividend payments can only be made at the jump times of an independent Poisson process. In the dual (spectrally positive Lévy) model, recent results have shown the optimality of a periodic barrier strategy, which pays dividends at Poissonian dividend-decision times, if and only if the surplus is above some level. In this paper, we show the optimality of this strategy for a spectrally negative Lévy process whose dual has a completely monotone Lévy density. The optimal strategies and value functions are concisely written in terms of the scale functions. Numerical results are also provided.

Suggested Citation

  • Noba, Kei & Pérez, José-Luis & Yamazaki, Kazutoshi & Yano, Kouji, 2018. "On optimal periodic dividend strategies for Lévy risk processes," Insurance: Mathematics and Economics, Elsevier, vol. 80(C), pages 29-44.
  • Handle: RePEc:eee:insuma:v:80:y:2018:i:c:p:29-44
    DOI: 10.1016/j.insmatheco.2018.02.004
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    References listed on IDEAS

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    13. Peter Carr & Helyette Geman, 2002. "The Fine Structure of Asset Returns: An Empirical Investigation," The Journal of Business, University of Chicago Press, vol. 75(2), pages 305-332, April.
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    Citations

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    Cited by:

    1. Avanzi, Benjamin & Lau, Hayden & Wong, Bernard, 2020. "Optimal periodic dividend strategies for spectrally positive Lévy risk processes with fixed transaction costs," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 315-332.
    2. Benjamin Avanzi & Hayden Lau & Bernard Wong, 2020. "Optimal periodic dividend strategies for spectrally positive L\'evy risk processes with fixed transaction costs," Papers 2003.13275, arXiv.org, revised May 2020.
    3. Benjamin Avanzi & Hayden Lau & Bernard Wong, 2020. "Optimal periodic dividend strategies for spectrally negative L\'evy processes with fixed transaction costs," Papers 2004.01838, arXiv.org, revised Dec 2020.
    4. Dong, Hua & Zhou, Xiaowen, 2019. "On a spectrally negative Lévy risk process with periodic dividends and capital injections," Statistics & Probability Letters, Elsevier, vol. 155(C), pages 1-1.
    5. Zbigniew Palmowski & Jos'e Luis P'erez & Budhi Arta Surya & Kazutoshi Yamazaki, 2019. "The Leland-Toft optimal capital structure model under Poisson observations," Papers 1904.03356, arXiv.org, revised Mar 2020.
    6. Benjamin Avanzi & Hayden Lau & Bernard Wong, 2020. "On the optimality of joint periodic and extraordinary dividend strategies," Papers 2006.00717, arXiv.org, revised Dec 2020.
    7. José-Luis Pérez & Kazutoshi Yamazaki, 2018. "Mixed Periodic-Classical Barrier Strategies for Lévy Risk Processes," Risks, MDPI, vol. 6(2), pages 1-39, April.
    8. Avanzi, Benjamin & Lau, Hayden & Wong, Bernard, 2021. "On the optimality of joint periodic and extraordinary dividend strategies," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1189-1210.
    9. Liu, Zhang & Chen, Ping & Hu, Yijun, 2020. "On the dual risk model with diffusion under a mixed dividend strategy," Applied Mathematics and Computation, Elsevier, vol. 376(C).
    10. Zbigniew Palmowski & José Luis Pérez & Kazutoshi Yamazaki, 2021. "Double continuation regions for American options under Poisson exercise opportunities," Mathematical Finance, Wiley Blackwell, vol. 31(2), pages 722-771, April.
    11. Chongrui Zhu, 2022. "On the closed-form expected NPVs of double barrier strategies for regular diffusions," Papers 2206.08922, arXiv.org, revised Dec 2022.
    12. Zbigniew Palmowski & Jos'e Luis P'erez & Kazutoshi Yamazaki, 2020. "Double continuation regions for American options under Poisson exercise opportunities," Papers 2004.03330, arXiv.org.
    13. Zbigniew Palmowski & José Luis Pérez & Budhi Arta Surya & Kazutoshi Yamazaki, 2020. "The Leland–Toft optimal capital structure model under Poisson observations," Finance and Stochastics, Springer, vol. 24(4), pages 1035-1082, October.

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