Advanced Search
MyIDEAS: Login to save this paper or follow this series

Localising temperature risk

Contents:

Author Info

  • Wolfgang Karl Härdle
  • Brenda López Cabrera
  • Ostap Okhrin
  • Weining Wang

Abstract

On the temperature derivative market, modeling temperature volatility is an important issue for pricing and hedging. In order to apply pricing tools of nancial mathematics, one needs to isolate a Gaussian risk factor. A conventional model for temperature dynamics is a stochastic model with seasonality and inter temporal autocorrelation. Empirical work based on seasonality and autocorrelation correction reveals that the obtained residuals are heteroscedastic with a periodic pattern. The object of this research is to estimate this het- eroscedastic function so that after scale normalisation a pure standardised Gaussian variable appears. Earlier work investigated this temperature risk in different locations and showed that neither parametric component functions nor a local linear smoother with constant smoothing parameter are flexible enough to generally describe the volatility process well. Therefore, we consider a local adaptive modeling approach to find at each time point, an optimal smooth- ing parameter to locally estimate the seasonality and volatility. Our approach provides a more flexible and accurate fitting procedure of localised temperature risk process by achieving excellent normal risk factors.

Download Info

If 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.
File URL: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2011-001.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2011-001.

as in new window
Length: 31 pages
Date of creation: Jan 2011
Date of revision:
Handle: RePEc:hum:wpaper:sfb649dp2011-001

Contact details of provider:
Postal: Spandauer Str. 1,10178 Berlin
Phone: +49-30-2093-5708
Fax: +49-30-2093-5617
Email:
Web page: http://sfb649.wiwi.hu-berlin.de
More information through EDIRC

Related research

Keywords: Weather derivatives; localising temperature residuals; seasonality; local model selection;

Find related papers by JEL classification:

References

No references listed on IDEAS
You can help add them by filling out this form.

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:hum:wpaper:sfb649dp2011-001. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (RDC-Team).

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.