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Can energy prices predict stock returns? An extreme bounds analysis

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  • Kim, Jae H.
  • Rahman, Md Lutfur
  • Shamsuddin, Abul

Abstract

We assess the predictive abilities of energy prices for future US stock market returns using Sala-i-Martin's (1997) extreme bounds analysis (EBA). The EBA results reveal that the predictive power of energy prices varies substantially across the regression models with different combinations of conditioning variables. Energy prices are not robust predictors for the stock returns in the whole sample period from June 1987 to April 2015. However, before the 2008 global financial crisis, energy prices exerted a moderate negative effect on future stock returns and their effects have become strongly positive afterwards. In general, the predictive power declines with the increase in forecast horizon and it varies considerably over time.

Suggested Citation

  • Kim, Jae H. & Rahman, Md Lutfur & Shamsuddin, Abul, 2019. "Can energy prices predict stock returns? An extreme bounds analysis," Energy Economics, Elsevier, vol. 81(C), pages 822-834.
    • Handle: RePEc:eee:eneeco:v:81:y:2019:i:c:p:822-834
    DOI: 10.1016/j.eneco.2019.05.029
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    Cited by:

    1. Naeem, Muhammad Abubakr & Balli, Faruk & Shahzad, Syed Jawad Hussain & de Bruin, Anne, 2020. "Energy commodity uncertainties and the systematic risk of US industries," Energy Economics, Elsevier, vol. 85(C).
    2. Guo, Li-Yang & Feng, Chao & Yang, Jun, 2022. "Can energy predict the regional prices of carbon emission allowances in China?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    3. Kamal, Javed Bin & Wohar, Mark, 2023. "Heterogenous responses of stock markets to covid related news and sentiments: Evidence from the 1st year of pandemic," International Economics, Elsevier, vol. 173(C), pages 68-85.
    4. Fijorek, Kamil & Jurkowska, Aleksandra & Jonek-Kowalska, Izabela, 2021. "Financial contagion between the financial and the mining industries – Empirical evidence based on the symmetric and asymmetric CoVaR approach," Resources Policy, Elsevier, vol. 70(C).
    5. Zhang, Hua & Chen, Jinyu & Shao, Liuguo, 2021. "Dynamic spillovers between energy and stock markets and their implications in the context of COVID-19," International Review of Financial Analysis, Elsevier, vol. 77(C).
    6. Michaela Vourvoulia & Athanasios Kampas, 2024. "Are democratic regime and the magnitude of the informal economy robust determinants of human impacts on the environment? An extreme bounds analysis," Economics and Politics, Wiley Blackwell, vol. 36(1), pages 611-629, March.
    7. Rahman, Md Lutfur & Hedström, Axel & Uddin, Gazi Salah & Kang, Sang Hoon, 2021. "Quantile relationship between Islamic and non-Islamic equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    8. César Castro & Rebeca Jiménez-Rodríguez & Renatas Kizys, 2023. "Time-Varying Relation between Oil Shocks and European Stock Market Returns," JRFM, MDPI, vol. 16(3), pages 1-28, March.
    9. Godwin Olasehinde-Williams & Oktay Özkan, 2022. "Is interest rate uncertainty a predictor of investment volatility? evidence from the wild bootstrap likelihood ratio approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 507-521, July.
    10. Xiao, Jihong & Wang, Yudong, 2022. "Good oil volatility, bad oil volatility, and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 953-966.
    11. Avik Sinha & Arshian Sharif & Arnab Adhikari & Ankit Sharma, 2022. "Dependence structure between Indian financial market and energy commodities: a cross-quantilogram based evidence," Annals of Operations Research, Springer, vol. 313(1), pages 257-287, June.
    12. Kim, Jae H. & Shamsuddin, Abul, 2023. "Stock market anomalies: An extreme bounds analysis," International Review of Financial Analysis, Elsevier, vol. 90(C).
    13. Nygaard, Knut & Sørensen, Lars Qvigstad, 2024. "Betting on war? Oil prices, stock returns, and extreme geopolitical events," Energy Economics, Elsevier, vol. 136(C).
    14. Tri Wahyu Adi, 2022. "The International Gas and Crude Oil Price Variability Effect on Indonesian Coal Mining Companies Listed at IDX," International Journal of Energy Economics and Policy, Econjournals, vol. 12(5), pages 1-10, September.
    15. Zhang, Xincheng, 2024. "Country-level energy-related uncertainties and stock market returns: Insights from the U.S. and China," Technological Forecasting and Social Change, Elsevier, vol. 204(C).
    16. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    17. Adekoya, Oluwasegun B. & Ogunbowale, Gideon O. & Akinseye, Ademola B. & Oduyemi, Gabriel O., 2021. "Improving the predictability of stock returns with global financial cycle and oil price in oil-exporting African countries," International Economics, Elsevier, vol. 168(C), pages 166-181.

    More about this item

    Keywords

    Energy prices; Stock return predictability; Extreme bounds analysis;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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