School of Science Seminar: Singular dividend optimization for a linear diffusion model with time-inconsistent preferences


2:00 PM - 3:00 PM

MB541, Math Building


  • Date: 7th Jan, 2021
  • Time: 14:00-15:00
  • Organizer: Department of Statistics & Actuarial
    Science School of Science
  • Speaker: Dr Jinxia Zhu
  • Venue: MB541, Math Building / Zoom Meeting

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With the advancement of behavioral economics, the use of exponential discounting for decision making in neoclassical economics has been questioned since it cannot provide a realistic way to explain certain decision-making behavior. The purpose of this paper is to investigate strategic decision making on dividend distribution policies of insurance companies when the management adopts a more realistic way for discounting, namely stochastic quasi-hyperbolic discounting. A game theoretic approach is adopted to establish economic equilibrium results, namely subgame perfect Markov equilibrium strategies. It is shown that (1) under certain mild technical conditions, the barrier strategy with an optimal barrier, which is widely used in the traditional approach to optimal dividend problems, is a perfect Markov equilibrium strategy, (2) the optimal barrier is lower than the barrier of an optimal strategy obtained from the respective time-consistent optimal dividend problem, and (3) the solution based on the barrier strategy does not exist in some situations.


Dr Jinxia Zhu
Associate Professor and Associate Head of School (Academics) in the School of Risk and Actuarial Studies, UNSW

She holds a PhD degree in Actuarial Science, and MSc and BA in Mathematics. Her main research interests lie in the areas of optimal control in insurance and finance, and risk theory. She has published in leading international journals in the fields of Actuarial Science, Applied Probability and Operations research including SIAM Journal on Control and Optimisation, Stochastic Processes and Their Applications, European Journal Operations Research, Journal of and Advance in Applied Probability, Insurance: Mathematics and Economics, etc.

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