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Forecasting carbon futures volatility : The predictive power of GARCH models with energy volatilities

  • Suk Joon Byun KAIST Business School, 85 Hoegiro, Dongdaemoon-gu, Seoul, 130-722 Korea
  • Hangjun Cho KAIST Business School, 85 Hoegiro, Dongdaemoon-gu, Seoul, 130-722 Korea
This article examines the volatility forecasting abilities of two approaches: one is GARCH-type model that uses carbon futures prices, and the other is an implied volatility from carbon options prices. Based on the results, we document that GARCH-type models perform better than an implied volatility. This result suggests that carbon options have little information about carbon futures due to their low trading volume. We also investigate whether the volatilities of energy markets, i.e., Brent oil, coal, natural gas, and electricity, forecast following day¡¯s carbon futures volatility. According to the results, we suggest that Brent oil and natural gas may be used to forecast the volatility of carbon futures.

  • Suk Joon Byun
  • Hangjun Cho
This article examines the volatility forecasting abilities of two approaches: one is GARCH-type model that uses carbon futures prices, and the other is an implied volatility from carbon options prices. Based on the results, we document that GARCH-type models perform better than an implied volatility. This result suggests that carbon options have little information about carbon futures due to their low trading volume. We also investigate whether the volatilities of energy markets, i.e., Brent oil, coal, natural gas, and electricity, forecast following day¡¯s carbon futures volatility. According to the results, we suggest that Brent oil and natural gas may be used to forecast the volatility of carbon futures.
Carbon futures,GARCH,Implied volatility,Forecasting,Energy market