Modeling temperature behaviors: Application to weather derivative valuation

Jr Wei Huang, Sharon S. Yang, Chuang Chang Chang

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


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.

Original languageEnglish
Pages (from-to)1152-1175
Number of pages24
JournalJournal of Futures Markets
Issue number9
StatePublished - Sep 2018


  • equilibrium pricing
  • long memory
  • temperature derivatives


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