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Risk contribution of crude oil to industry stock returns

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  • Yu, Honghai
  • Du, Donglei
  • Fang, Libing
  • Yan, Panpan

Abstract

Oil shock is an important source of risk and hence has a significant effect on the real economy and financial markets. The objective of this study is to explore the crude oil risk contribution to industry-level returns in the US stock market using the ADCC-ΔCoVaR model. We employ the Kolmogorov–Smirnov test to rank the contribution and then investigate the structural breakpoints using the Bai and Perron (2003) test. Our empirical results reveal that oil contributes the highest risk to the energy industry and the lowest risk to the Consumer Staples industry. We also find notable discrepancies between industries with regard to number of breakpoints and the break date. In particular, the rankings of the financial, materials, and utilities industries fluctuate dramatically across different sub-samples. In addition, the crude oil risk contribution was commonly larger across all these industries during the 2008 crisis period. Our findings are helpful to investors, market participants, and policy makers.

Suggested Citation

  • Yu, Honghai & Du, Donglei & Fang, Libing & Yan, Panpan, 2018. "Risk contribution of crude oil to industry stock returns," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 179-199.
  • Handle: RePEc:eee:reveco:v:58:y:2018:i:c:p:179-199
    DOI: 10.1016/j.iref.2018.03.009
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    2. Abuzayed, Bana & Bouri, Elie & Al-Fayoumi, Nedal & Jalkh, Naji, 2021. "Systemic risk spillover across global and country stock markets during the COVID-19 pandemic," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 180-197.
    3. Ying-Ying Shen & Zhi-Qiang Jiang & Jun-Chao Ma & Gang-Jin Wang & Wei-Xing Zhou, 2022. "Sector connectedness in the Chinese stock markets," Empirical Economics, Springer, vol. 62(2), pages 825-852, February.
    4. Vidal-Llana, Xenxo & Uribe, Jorge M. & Guillén, Montserrat, 2023. "European stock market volatility connectedness: The role of country and sector membership," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    5. Daniel Ştefan Armeanu & Camelia Cătălina Joldeş & Ştefan Cristian Gherghina, 2019. "On the Linkage between the Energy Market and Stock Returns: Evidence from Romania," Energies, MDPI, vol. 12(8), pages 1-21, April.
    6. Liu, Xiang-dong & Pan, Fei & Cai, Wen-li & Peng, Rui, 2020. "Correlation and risk measurement modeling: A Markov-switching mixed Clayton copula approach," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    7. Abuzayed, Bana & Al-Fayoumi, Nedal, 2021. "Risk spillover from crude oil prices to GCC stock market returns: New evidence during the COVID-19 outbreak," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    8. Chan, Kam C. & Chan, Leo H. & Nguyen, Chi M., 2020. "Forecasting oil futures market volatility in a financialized world: Why speculative activities matter," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    9. Salisu, Afees A. & Swaray, Raymond & Oloko, Tirimisiyu F., 2019. "Improving the predictability of the oil–US stock nexus: The role of macroeconomic variables," Economic Modelling, Elsevier, vol. 76(C), pages 153-171.
    10. Pal, Debdatta & Mitra, Subrata K., 2019. "Correlation dynamics of crude oil with agricultural commodities: A comparison between energy and food crops," Economic Modelling, Elsevier, vol. 82(C), pages 453-466.
    11. Yin, Libo & Feng, Jiabao & Liu, Li & Wang, Yudong, 2019. "It's not that important: The negligible effect of oil market uncertainty," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 62-84.
    12. Zhenhua Liu & Zhihua Ding & Tao Lv & Jy S. Wu & Wei Qiang, 2019. "Financial factors affecting oil price change and oil-stock interactions: a review and future perspectives," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 95(1), pages 207-225, January.

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    More about this item

    Keywords

    Crude oil market; Industry stock returns; Risk contribution; ADCC-ΔCoVaR;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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