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Optimal futures hedging for energy commodities: An application of the GAS model
Author(s) -
Xu Yingying,
Lien Donald
Publication year - 2020
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.22118
Subject(s) - futures contract , copula (linguistics) , autoregressive conditional heteroskedasticity , econometrics , autoregressive model , volatility (finance) , economics , natural gas , spot contract , hedge , ordinary least squares , value at risk , financial economics , risk management , engineering , ecology , biology , management , waste management
Abstract This paper applies generalized autoregressive score‐driven (GAS) models to futures hedging of crude oil and natural gas. For both commodities, the GAS framework captures the marginal distributions of spot and futures returns and corresponding dynamic copula correlations. We compare within‐sample and out‐of‐sample hedging effectiveness of GAS models against constant ordinary least square (OLS) strategy and time‐varying copula‐based GARCH models in terms of volatility reduction and Value at Risk reduction. We show that the constant OLS hedge ratio is not inherently inferior to the time‐varying alternatives. Nonetheless, GAS models tend to exhibit better hedging effectiveness than other strategies, particularly for natural gas.