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Modeling global and local dependence in a pair of commodity forward curves with an application to the US natural gas and heating oil markets

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  • Ohana, Steve

Abstract

The goal of this paper is to present a model for the joint evolution of correlated commodity forward curves. Each forward curve is directed by two state variables, namely slope and level, and the model is meant to capture both the local and global dependence structures between slopes and levels. Our framework can be interpreted as an extension of the concept of cointegration to forward curves. The model is applied to a US database of heating oil and natural gas futures prices over the period February 2000-February 2009. We find the long-run slope and level relationships between natural gas and heating oil markets, analyze the lead and lag properties between the two energy commodities, the volatilities and correlations between their daily co-movements and evaluate the robustness of these observations to the turmoil experienced by energy markets since 2003.

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  • Ohana, Steve, 2010. "Modeling global and local dependence in a pair of commodity forward curves with an application to the US natural gas and heating oil markets," Energy Economics, Elsevier, vol. 32(2), pages 373-388, March.
  • Handle: RePEc:eee:eneeco:v:32:y:2010:i:2:p:373-388
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    2. Ji, Qiang & Zhang, Hai-Ying & Geng, Jiang-Bo, 2018. "What drives natural gas prices in the United States? – A directed acyclic graph approach," Energy Economics, Elsevier, vol. 69(C), pages 79-88.
    3. Zolotko, Mikhail & Okhrin, Ostap, 2014. "Modelling the general dependence between commodity forward curves," Energy Economics, Elsevier, vol. 43(C), pages 284-296.
    4. Moting Su & Zongyi Zhang & Ye Zhu & Donglan Zha & Wenying Wen, 2019. "Data Driven Natural Gas Spot Price Prediction Models Using Machine Learning Methods," Energies, MDPI, vol. 12(9), pages 1-17, May.
    5. Sheng-Hung Chen & Song-Zan Chiou-Wei & Zhen Zhu, 2022. "Stochastic seasonality in commodity prices: the case of US natural gas," Empirical Economics, Springer, vol. 62(5), pages 2263-2284, May.

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