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Modeling temperature behaviors: Application to weather derivative valuation
Author(s) -
Huang JrWei,
Yang Sharon S.,
Chang ChuangChang
Publication year - 2018
Publication title -
journal of futures markets
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.88
H-Index - 55
eISSN - 1096-9934
pISSN - 0270-7314
DOI - 10.1002/fut.21923
Subject(s) - autoregressive fractionally integrated moving average , valuation (finance) , autoregressive conditional heteroskedasticity , econometrics , derivative (finance) , economics , environmental science , computer science , meteorology , financial economics , long memory , accounting , physics , volatility (finance)
This article investigates temperature behavior to develop a temperature model. The proposed ARFIMA Seasonal GARCH model that allows for long memory effects and other important temperature properties provides better goodness of fits and forecasting accuracy using daily average temperatures in six U.S. cities. The effect of temperature behavior on pricing temperature derivatives is analyzed. We propose an equilibrium option pricing framework for HDD and CDD forward and option contracts under the ARFIMA Seasonal GARCH model. The investigation of temperature properties and the valuation framework in this study contributes to the development of a standardized temperature model for weather derivative markets.