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Event Study of Energy Price Volatility: An Application of Distributional Event Response Model

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  • Ye, Shiyu
  • Karali, Berna
  • Ramirez, Octavio A.

Abstract

We apply the Distributional Event Response Model (DERM), which is appropriate in studying relatively slowly-evolving information events, to nineteen years of daily crude oil futures returns and volatility to analyze the pattern of market responses to selected events. The results show that all the events considered have statistically significant effects on crude oil futures price volatility. The U.S. invasion of Iraq in 2003 and the bankruptcy filing of Lehman Brothers in 2008 are found to have the largest impacts on both daily returns and volatility. In addition, the location and duration of event windows vary across different event. Generally, the largest volatility response to an event is observed after several months following the event, suggesting that simply using an event-day dummy variable would hinder discovering the actual market responses to slowly-evolving events.

Suggested Citation

  • Ye, Shiyu & Karali, Berna & Ramirez, Octavio A., 2014. "Event Study of Energy Price Volatility: An Application of Distributional Event Response Model," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170207, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea14:170207
    DOI: 10.22004/ag.econ.170207
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    References listed on IDEAS

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    1. Kaufmann, Robert K., 2011. "The role of market fundamentals and speculation in recent price changes for crude oil," Energy Policy, Elsevier, vol. 39(1), pages 105-115, January.
    2. Thomas W. Hertel & Jayson Beckman, 2011. "Commodity Price Volatility in the Biofuel Era: An Examination of the Linkage between Energy and Agricultural Markets," NBER Chapters, in: The Intended and Unintended Effects of US Agricultural and Biotechnology Policies, pages 189-221, National Bureau of Economic Research, Inc.
    3. Randal R. Rucker & Walter N. Thurman & Jonathan K. Yoder, 2005. "Estimating the Structure of Market Reaction to News: Information Events and Lumber Futures Prices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(2), pages 482-500.
    4. Serra, Teresa, 2011. "Volatility spillovers between food and energy markets: A semiparametric approach," Energy Economics, Elsevier, vol. 33(6), pages 1155-1164.
    5. Karali, Berna & Ramirez, Octavio A., 2014. "Macro determinants of volatility and volatility spillover in energy markets," Energy Economics, Elsevier, vol. 46(C), pages 413-421.
    6. repec:aen:journl:2001v22-03-a01 is not listed on IDEAS
    7. Berna Karali & Gabriel J. Power, 2013. "Short- and Long-Run Determinants of Commodity Price Volatility," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(3), pages 724-738.
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    Cited by:

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    3. Chen, Shengming & Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "The Russia–Ukraine war and energy market volatility: A novel application of the volatility ratio in the context of natural gas," Resources Policy, Elsevier, vol. 85(PA).
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    6. Ma, Richie Ruchuan & Xiong, Tao & Bao, Yukun, 2021. "The Russia-Saudi Arabia oil price war during the COVID-19 pandemic," Energy Economics, Elsevier, vol. 102(C).

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