Weather forecasting for weather derivatives : [revised version: January 2, 2004]
- We take a simple time-series approach to modeling and forecasting daily average temperature in U.S. cities, and we inquire systematically as to whether it may prove useful from the vantage point of participants in the weather derivatives market. The answer is, perhaps surprisingly, yes. Time-series modeling reveals conditional mean dynamics, and crucially, strong conditional variance dynamics, in daily average temperature, and it reveals sharp differences between the distribution of temperature and the distribution of temperature surprises. As we argue, it also holds promise for producing the long-horizon predictive densities crucial for pricing weather derivatives, so that additional inquiry into time-series weather forecasting methods will likely prove useful in weather derivatives contexts.
| Author: | Sean D. Campbell, Francis X. Diebold |
|---|---|
| URN: | urn:nbn:de:hebis:30-10621 |
| Parent Title (German): | Center for Financial Studies (Frankfurt am Main): CFS working paper series ; No. 2004,10 |
| Series (Serial Number): | CFS working paper series (2004, 10) |
| Document Type: | Working Paper |
| Language: | English |
| Year of Completion: | 2004 |
| Year of first Publication: | 2004 |
| Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
| Release Date: | 2005/06/13 |
| Tag: | financial derivatives; hedging; insurance; risk management; seasonality; temperature |
| GND Keyword: | USA; Derivat, Wertpapier; Zeitreihe; Wettervorhersage |
| Issue: | revised version: January 2, 2004 |
| Page Number: | 30 |
| HeBIS-PPN: | 221931112 |
| Institutes: | Wissenschaftliche Zentren und koordinierte Programme / Center for Financial Studies (CFS) |
| Dewey Decimal Classification: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
| Licence (German): |  Deutsches Urheberrecht |
