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Linkages Between Oil Price Shocks and Stock Returns Revisited

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  • Firmin Doko Tchatoka

    (School of Economics, University of Adelaide)

  • Virginie Masson

    (School of Economics, University of Adelaide)

  • Sean Parry

    (School of Economics, University of Adelaide)

Abstract

In this paper, we revisit the debate on the relationship between oil price shocks and stock market returns by replicating the quantile-on-quantile (QQ) regression model for the US stock market in Sim and Zhou (2015, Journal of Banking and Finance), and extending it to 15 countries. The classification of these countries as oil importers or oil exporters depends on their net position in crude oil trade. Our results indicate that the finding by Sim and Zhou (2015) that large negative oil price shocks can bolster stock returns when markets are performing well is only partially supported by the three largest oil importers in our sample-China, Japan and India-during the period 1988:1-2007:12. However, when extending the study to more recent data (period 1988:1-2016:12), we find that China and India experience higher returns when markets perform well and there is a large positive oil price shock. Also, large positive oil price shocks often lead to higher stock market returns when markets perform well for both oil exporting countries-Canada, Russia, Norway-and moderately oil dependent countries-such as Malaysia, Philippines and Thailand. These findings highlight that the relationship between the distributions of oil price shocks and stock market returns is not stable over time in most countries studied. Furthermore, the asymmetric effect of oil price shocks observed in the US market by Sim and Zhou (2015) is less evident in most countries for both the baseline and extended periods.

Suggested Citation

  • Firmin Doko Tchatoka & Virginie Masson & Sean Parry, 2018. "Linkages Between Oil Price Shocks and Stock Returns Revisited," School of Economics and Public Policy Working Papers 2018-01, University of Adelaide, School of Economics and Public Policy.
  • Handle: RePEc:adl:wpaper:2018-01
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    4. Katarzyna Kuziak & Joanna Górka, 2023. "Dependence Analysis for the Energy Sector Based on Energy ETFs," Energies, MDPI, vol. 16(3), pages 1-30, January.
    5. Mushtaq Hussain Khan & Junaid Ahmed & Mazhar Mughal & Imtiaz Hussain Khan, 2023. "Oil price volatility and stock returns: Evidence from three oil‐price wars," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 3162-3182, July.
    6. Chen, Qitong & Zhu, Huiming & Yu, Dongwei & Hau, Liya, 2022. "How does investor attention matter for crude oil prices and returns? Evidence from time-frequency quantile causality analysis," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    7. 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.
    8. Rehman, Mobeen Ur & Ahmad, Nasir & Vo, Xuan Vinh, 2022. "Asymmetric multifractal behaviour and network connectedness between socially responsible stocks and international oil before and during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    9. Mushtaq Hussain Khan & Junaid Ahmed & Mazhar Mughal, 2022. "Dependence between oil price changes and sectoral stock returns in Pakistan: Evidence from a quantile regression approach," Energy & Environment, , vol. 33(2), pages 315-331, March.
    10. Zhao-Yong Sun & Wei-Chiao Huang, 2023. "The effects of unexpected crude oil price shocks on Chinese stock markets," Economic Change and Restructuring, Springer, vol. 56(3), pages 1683-1697, June.
    11. Sanginabadi, Bahram, 2021. "Oil and Mortality," OSF Preprints j2xqw, Center for Open Science.
    12. Hadhri, Sinda, 2021. "The nexus, downside risk and asset allocation between oil and Islamic stock markets: A cross-country analysis," Energy Economics, Elsevier, vol. 101(C).
    13. Aviral Kumar Tiwari & Samia Nasreen & Subhan Ullah & Muhammad Shahbaz, 2021. "Analysing spillover between returns and volatility series of oil across major stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2458-2490, April.
    14. Balcilar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2019. "Quantile relationship between oil and stock returns: Evidence from emerging and frontier stock markets," Energy Policy, Elsevier, vol. 134(C).
    15. Xie, Qichang & Tang, Guoqiang, 2022. "Do market conditions interfere with the transmission of uncertainty from oil market to stock market? Evidence from a modified quantile-on-quantile approach," Energy Economics, Elsevier, vol. 114(C).
    16. Sheng Fang & Paul Egan, 2021. "Tail dependence between oil prices and China's A‐shares: Evidence from firm‐level data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1469-1487, January.
    17. Seuk Wai Phoong & Masnun Al Mahi & Seuk Yen Phoong, 2023. "A Markov Switching Approach in Assessing Oil Price and Stock Market Nexus in the Last Decade: The Impact of the COVID-19 Pandemic," SAGE Open, , vol. 13(1), pages 21582440231, February.
    18. Muhammad Kamran Khan & Jian‐Zhou Teng & Muhammad Imran Khan & Muhammad Fayaz Khan, 2023. "Stock market reaction to macroeconomic variables: An assessment with dynamic autoregressive distributed lag simulations," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2436-2448, July.
    19. Jiang, Yonghong & Feng, Qidi & Mo, Bin & Nie, He, 2020. "Visiting the effects of oil price shocks on exchange rates: Quantile-on-quantile and causality-in-quantiles approaches," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    20. Moghaddam, Mohsen Bakhshi, 2023. "The relationship between oil price changes and economic growth in Canadian provinces: Evidence from a quantile-on-quantile approach," Energy Economics, Elsevier, vol. 125(C).
    21. Ma, Yiqun & Wang, Junhao, 2021. "Time-varying spillovers and dependencies between iron ore, scrap steel, carbon emission, seaborne transportation, and China's steel stock prices," Resources Policy, Elsevier, vol. 74(C).
    22. Ma, Yiqun, 2021. "Do iron ore, scrap steel, carbon emission allowance, and seaborne transportation prices drive steel price fluctuations?," Resources Policy, Elsevier, vol. 72(C).
    23. Deheri, Abdhut & Ramachandran, M., 2023. "Does Indian economy asymmetrically respond to oil price shocks?," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    24. Mo, Bin & Chen, Cuiqiong & Nie, He & Jiang, Yonghong, 2019. "Visiting effects of crude oil price on economic growth in BRICS countries: Fresh evidence from wavelet-based quantile-on-quantile tests," Energy, Elsevier, vol. 178(C), pages 234-251.
    25. Joo, Young C. & Park, Sung Y., 2021. "The impact of oil price volatility on stock markets: Evidences from oil-importing countries," Energy Economics, Elsevier, vol. 101(C).

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    More about this item

    Keywords

    Oil prices; stock returns; Quantile regression;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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