TY  - JOUR
AU  - Campbell,Sean D.
AU  - Diebold,Francis X.
TI  - Weather Forecasting for Weather Derivatives
JF  - National Bureau of Economic Research Working Paper Series
VL  - No. 10141
PY  - 2003
Y2  - December 2003
UR  - http://www.nber.org/papers/w10141
L1  - http://www.nber.org/papers/w10141.pdf
N1  - Author contact info:
Sean Campbell
Division of Research and Statistics
Federal Reserve Board
20th Street and Constitution Avenue
Washington, DC 20551
Tel: 202.452.3760
Fax: 202.728.5887
E-Mail: sean.d.campbell@frb.gov

Francis X. Diebold
Department of Economics
University of Pennsylvania
3718 Locust Walk
Philadelphia, PA  19104-6297
Tel: 215/898-1507
Fax: 212/573-4217
E-Mail: fdiebold@sas.upenn.edu
AB  - 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 both strong conditional mean dynamics and conditional variance dynamics in daily average temperature, and it reveals sharp differences between the distribution of temperature and the distribution of temperature surprises. The approach can easily be used to produce not only short-horizon point forecasts, but also the long-horizon density forecasts of maximal relevance in weather derivatives contexts. We produce and evaluate both, with some success. We conclude that additional inquiry into nonstructural weather forecasting methods will likely prove useful in weather derivatives contexts.
ER  -