Classical, Singular, and Impulse Stochastic Control for the Optimal Dividend Policy when There is Regime Switching

49 Pages Posted: 1 Jun 2008

See all articles by Luz R. Sotomayor

Luz R. Sotomayor

Georgia State University - Department of Risk Management and Insurance

Abel Cadenillas

University of Alberta - Department of Mathematical and Statistical Sciences

Abstract

Motivated by economic and empirical arguments, we consider a company whose cash reservoir is affected by macroeconomic conditions. Specifically, we model the cash reservoir as a Brownian motion with drift and volatility modulated by an observable continuous-time Markov chain that represents the regime of the economy. The objective of the management is to select the dividend policy that maximizes the expected total discounted dividend payments to be received by the shareholders. We study three different cases: bounded dividend rates, unbounded dividend rates, and the case in which there are fixed costs and taxes associated to the dividend payments. These cases generate, respectively, problems of classical stochastic control with regime switching, singular stochastic control with regime switching,and stochastic impulse control with regime switching (a new problem in the stochastic control literature). We solve these problems, and obtain the first analytical solutions for the optimal dividend policy in the presence of business cycles. Our results shows, among other things, that the optimal dividend policy depends strongly on macroeconomic conditions.

Keywords: Business cycles, Dividend policy, Stochastic control with regime switching

JEL Classification: G35, E32, C61

Suggested Citation

Sotomayor, Luz Rocío and Cadenillas, Abel, Classical, Singular, and Impulse Stochastic Control for the Optimal Dividend Policy when There is Regime Switching. Available at SSRN: https://ssrn.com/abstract=1139444 or http://dx.doi.org/10.2139/ssrn.1139444

Luz Rocío Sotomayor

Georgia State University - Department of Risk Management and Insurance ( email )

35 Broad Street
P.O. Box 4036
Atlanta, GA 30302-4036
United States
404-4137470 (Phone)
404-4137499 (Fax)

HOME PAGE: http://www.rmi.gsu.edu

Abel Cadenillas (Contact Author)

University of Alberta - Department of Mathematical and Statistical Sciences ( email )

Edmonton, Alberta T6G 2G1
Canada
(780) 492-0572 (Phone)
(780) 492-6826 (Fax)

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
444
Abstract Views
1,832
rank
73,443
PlumX Metrics