A possible way of estimating options with stable distributed underlying asset prices
C. Tsibiridi and
C. Atkinson
Applied Mathematical Finance, 2004, vol. 11, issue 1, 51-75
Abstract:
Option pricing theory is considered when the underlying asset price satisfies a stochastic differential equation which is driven by random motions generated by stable distributions. The properties of the stable distributions are discussed and their connection with the theory of fractional Brownian motion is noted. This approach attempts to generalize the classical Black-Scholes formulation, to allow for the presence of fat tails in the distribution of log prices which leads to a diffusion equation involving fractional Brownian motion. The resulting option pricing via a hedging strategy approach is independently derived by constructing a backward Kolmogorov equation for a simple trinomial model where the probabilities are assumed to satisfy a particular fractional Taylor series due to Dzherbashyan and Nersesyan. To effect this development, some knowledge of fractional integration and differentiation is required so this is briefly reviewed. Consideration is also given to a different hedging strategy approach leading to a fractional Black-Scholes equation involving the market price of risk. Modification to the model is also considered such as the impact of transaction costs. A simple example of American options is also considered.
Keywords: stable distributions; fractional Taylor series; fractional Black-Scholes equation (search for similar items in EconPapers)
Date: 2004
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/1350486042000190331 (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:11:y:2004:i:1:p:51-75
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAMF20
DOI: 10.1080/1350486042000190331
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 ().