Pricing and hedging of long-term futures and forward contracts by a three-factor model
AbstractThis paper demonstrates the pricing and hedging efficiency of a three-factor stochastic mean reversion Gaussian model of commodity prices using oil and copper futures and forward contracts. The model is estimated using NYMEX WTI (light sweet crude oil) and LME Copper futures prices and is shown to fit the data well. Furthermore, it shows how to hedge based on a three-factor model and confirms that using three different futures contracts to hedge long-term contracts outperforms the traditional parallel hedge based on a single futures position by time series data and simulation. It also finds that the three-factor model outperforms the two-factor version with respect to the replication of actual term structures and that stochastic mean reversion models outperform constant mean reversion models in Out of Sample hedges.
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 Quantitative Finance.
Volume (Year): 12 (2012)
Issue (Month): 12 (December)
Contact details of provider:
Web page: http://www.tandfonline.com/RQUF20
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Takashi Kato & Jun Sekine & Hiromitsu Yamamoto, 2014. "A One-Factor Conditionally Linear Commodity Pricing Model under Partial Information," Asia-Pacific Financial Markets, Springer, vol. 21(2), pages 151-174, May.
- Takashi Kato & Jun Sekine & Hiromitsu Yamamoto, 2014. "A One-Factor Conditionally Linear Commodity Pricing Model under Partial Information," Papers 1406.4275, arXiv.org.
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.