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Spillovers and Correlation Among Energy Futures Markets

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  • Alberto Manelli
  • Roberta Pace
  • Maria Leone

Abstract

In recent years the economic risk has increased for all entities. One form of risk that has been consistently felt is exposure to fluctuations in raw material prices. The volatility of both financial and commodities markets is the subject of considerable attention. In particular, volatility in the energy commodities markets has become very important in recent years on tension on the commodity markets. In general, we refer to commodity price fluctuation recorded in 2009 and 2012-2013. Instead, analyzing energy commodities markets in more detail, we refer to price increases recorded in 2008, 2014 and 2022. For example, in 2014 and 2022 the Russia-Ukraine conflict had significantly consequences and repercussions on the price of natural gas and all commodity energy. Volatility is a factor of market instability as it measures risk. For this reason, attracts great attention for policy makers and financial market participants. From this premises we intend to estimate the appropriate model to analyze the volatility and correlation between the different energy commodities considered. The purpose of the paper is to analyze the presence and extent of volatility transmission in energy markets: Crude oil, Natural gas, Gasoline and Heating oil. Finally, we perform a rolling estimation and forecasting of a model. The results show a significantly volatility spillovers effects and large GARCH affects for all markets. The study provides evidence for a high level of integration in energy commodity derivatives markets.

Suggested Citation

  • Alberto Manelli & Roberta Pace & Maria Leone, 2024. "Spillovers and Correlation Among Energy Futures Markets," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 15(4), pages 35-45, October.
    • Handle: RePEc:jfr:ijfr11:v:15:y:2024:i:4:p:35-45
    DOI: 10.5430/ijfr.v15n4p35
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    References listed on IDEAS

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    1. Shrestha, Keshab, 2014. "Price discovery in energy markets," Energy Economics, Elsevier, vol. 45(C), pages 229-233.
    2. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    3. Deng, S.J. & Oren, S.S., 2006. "Electricity derivatives and risk management," Energy, Elsevier, vol. 31(6), pages 940-953.
    4. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
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    Cited by:

    1. Samarakoon, S.M.R.K. & Pradhan, Rudra P., 2026. "How do return and volatility spillovers shape futures markets? Insights from index, commodity, and carbon emission futures," Renewable Energy, Elsevier, vol. 256(PD).

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