IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v81y2019icp822-834.html
   My bibliography  Save this article

Can energy prices predict stock returns? An extreme bounds analysis

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988319301835
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2019.05.029?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. 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).
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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).
    13. 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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:81:y:2019:i:c:p:822-834. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.