TY  - UNPD
A1  - Campbell, Sean D.
A1  - Diebold, Francis X.
T1  - Weather forecasting for weather derivatives : [revised version: January 2, 2004]
T2  - Center for Financial Studies (Frankfurt am Main): CFS working paper series ; No. 2004,10
N2  - 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.
T3  - CFS working paper series - 2004, 10 
KW  - risk management
KW  - hedging
KW  - insurance
KW  - seasonality
KW  - temperature
KW  - financial derivatives
KW  - USA
KW  - Derivat, Wertpapier
KW  - Zeitreihe
KW  - Wettervorhersage
Y1  - 2004
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/4429
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30-10621
IS  - revised version: January 2, 2004
ER  -