Abstract
Motivated by previous papers with conventional models of Geometric Brownian Motion (Hereafter GBM) or Mean-Reverting (Hereafter MR), we discuss the classical investment timing problem in this paper by assuming the output price follows Heston-GBM process. That is, constant volatility in the classical GBM or MR framework is replaced by stochastic volatility in Heston-GBM model. We first derive the asymptotic solution for the investment timing problem. Then the impacts of stochastic volatility on trigger prices and the range of inaction are demonstrated by numerical simulation. Lastly, we examine the analytical properties of trigger prices and the range of inaction quantitatively as well as qualitatively.
Highlights
In the real world, most investment decisions are made in an uncertain background and are costly to reverse in the future
We will introduce our model in detail for the sake of intactness though it is an extension to the standard models to study entry and exit decisions under uncertainty, which proposed by Dixit and Tsekrekos
Many investment decisions of firms such as when to invest in an emerging market or whether to expand the capacity have been studied by many researches, which involve irreversible investment and uncertainty about demand, cost or competition, etc
Summary
Most investment decisions are made in an uncertain background and are costly to reverse in the future. Many researchers spent much time and energy to investigate this area from different aspects, and a number of new and useful results have been achieved Within these papers, Amir and Lambson [7] constructed an infinite-horizon, stochastic model of entry and exit with sunk costs and imperfect competition. Amir and Lambson [7] constructed an infinite-horizon, stochastic model of entry and exit with sunk costs and imperfect competition They find that for the general dynamic stochastic game, there exists a sub-game perfect Nash equilibrium as a limit of finite-horizon equilibria, which has a relatively simple structure characterized by two numbers per finite history.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
