• DocumentCode
    592461
  • Title

    Optimal dividend payment problems in piecewise-deterministic compound Poisson risk models

  • Author

    Runhuan Feng ; Shuaiqi Zhang ; Chao Zhu

  • Author_Institution
    Dept. of Math. Sci., Univ. of Wisconsin-Milwaukee, Milwaukee, WI, USA
  • fYear
    2012
  • fDate
    10-13 Dec. 2012
  • Firstpage
    7309
  • Lastpage
    7314
  • Abstract
    This work deals with an optimal dividend payment problem for a piecewise-deterministic compound Poisson insurance risk model. The objective is to maximize the expected discounted dividend payout up to the time of ruin. When the dividend payment rate is restricted, the value function is shown to be a solution of the corresponding Hamilton-Jacobi-Bellman equation, which in turn leads to a tractable methodology to find an optimal threshold dividend payment policy. For the case of unrestricted payment rate, the value function and an optimal barrier strategy are determined explicitly with exponential claim size distributions. A comparison of two examples is provided to illustrate the main results.
  • Keywords
    Poisson distribution; exponential distribution; insurance; optimisation; Hamilton-Jacobi-Bellman equation; dividend payment rate; expected discounted dividend payout; exponential claim size distributions; optimal barrier strategy; optimal dividend payment problems; optimal threshold dividend payment policy; piecewise-deterministic compound Poisson insurance risk model; unrestricted payment rate; value function; Compounds; Educational institutions; Equations; Insurance; Mathematical model; Process control; Stochastic processes; Hamilton-Jacobi-Bellman equation; Piecewise-deterministic compound Poisson model; barrier strategy; quasi-variational inequality; threshold strategy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
  • Conference_Location
    Maui, HI
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4673-2065-8
  • Electronic_ISBN
    0743-1546
  • Type

    conf

  • DOI
    10.1109/CDC.2012.6426672
  • Filename
    6426672