Deterministic versus stochastic volatility: implications for option pricing models
AbstractThe Black-Scholes (1973) option pricing model (BSOPM) rests on the assumption that the variance of stock returns is deterministic. However, if stock return volatility is a stochastic process, then the present form of commonly used option pricing models is misspecified and arbitrage-based arguments are invalid. The purpose of this paper is to investigate whether implied stock return volatility is deterministic (with non-linear dependencies) or stochastic. Correlation dimensions are computed using the method of Grassberger and Procaccia (1983) and simple bootstrapping techniques are applied in order to distinguish stochastic from deterministic systems. Results reported herein add support to the growing literature on preference-based stochastic volatility models and generally reject the notion of deterministic volatility.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Financial Economics.
Volume (Year): 7 (1997)
Issue (Month): 5 ()
Contact details of provider:
Web page: http://www.tandfonline.com/RAFE20
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Catherine Kyrtsou & Costas Vorlow, 2008.
"Modelling non-linear comovements between time series,"
2008_01, Durham University Business School.
- Kyrtsou, Catherine & Vorlow, Costas, 2009. "Modelling non-linear comovements between time series," Journal of Macroeconomics, Elsevier, vol. 31(1), pages 200-211, March.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.