Option Valuation with a Discrete-Time Double Markovian Regime-Switching Model
Tak Kuen Siu,
Eric S. Fung and
Michael K. Ng
Applied Mathematical Finance, 2011, vol. 18, issue 6, 473-490
Abstract:
This article develops an option valuation model in the context of a discrete-time double Markovian regime-switching (DMRS) model with innovations having a generic distribution. The DMRS model is more flexible than the traditional Markovian regime-switching model in the sense that the drift and the volatility of the price dynamics of the underlying risky asset are modulated by two observable, discrete-time and finite-state Markov chains, so that they are not perfectly correlated. The states of each of the chains represent states of proxies of (macro)economic factors. Here we consider the situation that one (macro)economic factor is caused by the other (macro)economic factor. The market model is incomplete, and so there is more than one equivalent martingale measure. We employ a discrete-time version of the regime-switching Esscher transform to determine an equivalent martingale measure for valuation. Different parametric distributions for the innovations of the price dynamics of the underlying risky asset are considered. Simulation experiments are conducted to illustrate the implementation of the model and to document the impacts of the macroeconomic factors described by the chains on the option prices under various different parametric models for the innovations.
Date: 2011
References: Add references at CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://hdl.handle.net/10.1080/1350486X.2011.578457 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:apmtfi:v:18:y:2011:i:6:p:473-490
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAMF20
DOI: 10.1080/1350486X.2011.578457
Access Statistics for this article
Applied Mathematical Finance is currently edited by Professor Ben Hambly and Christoph Reisinger
More articles in Applied Mathematical Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().