IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v40y2021ics1544612320307947.html
   My bibliography  Save this article

Stock return predictability over four centuries: The role of commodity returns

Author

Listed:
  • Iyke, Bernard Njindan
  • Ho, Sin-Yu

Abstract

We merge two unique historical datasets on commodity and stock prices covering four centuries and three leading stock markets (Netherlands, UK, and US) to show that, consistent with theoretical predictions, commodity returns can predict stock returns. We show that about 64% and 56% of the commodity returns can predict stock returns in-sample and out-of-sample, respectively. Aggregating commodity returns by market, returns from agriculture, energy, and livestock and meat markets appear to consistently predict stock returns. These results are robust to recessions and expansions.

Suggested Citation

  • Iyke, Bernard Njindan & Ho, Sin-Yu, 2021. "Stock return predictability over four centuries: The role of commodity returns," Finance Research Letters, Elsevier, vol. 40(C).
  • Handle: RePEc:eee:finlet:v:40:y:2021:i:c:s1544612320307947
    DOI: 10.1016/j.frl.2020.101711
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612320307947
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2020.101711?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.

    References listed on IDEAS

    as
    1. Ben Jacobsen & Ben R. Marshall & Nuttawat Visaltanachoti, 2019. "Stock Market Predictability and Industrial Metal Returns," Management Science, INFORMS, vol. 65(7), pages 3026-3042, July.
    2. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    3. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    4. Joakim Westerlund & Paresh Narayan, 2015. "Testing for Predictability in Conditionally Heteroskedastic Stock Returns," Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 342-375.
    5. Andrew Ang & Geert Bekaert, 2007. "Stock Return Predictability: Is it There?," The Review of Financial Studies, Society for Financial Studies, vol. 20(3), pages 651-707.
    6. Bernard Njindan Iyke, 2020. "The Disease Outbreak Channel of Exchange Rate Return Predictability: Evidence from COVID-19," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(10), pages 2277-2297, August.
    7. Charles R. Hickson & John D. Turner & Qing Ye, 2011. "The rate of return on equity across industrial sectors on the British stock market, 1825–70," Economic History Review, Economic History Society, vol. 64(4), pages 1218-1241, November.
    8. Golez, Benjamin & Koudijs, Peter, 2018. "Four centuries of return predictability," Journal of Financial Economics, Elsevier, vol. 127(2), pages 248-263.
    9. Westerlund, Joakim & Narayan, Paresh Kumar, 2012. "Does the choice of estimator matter when forecasting returns?," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2632-2640.
    10. David I. Harvey & Neil M. Kellard & Jakob B. Madsen & Mark E. Wohar, 2010. "The Prebisch-Singer Hypothesis: Four Centuries of Evidence," The Review of Economics and Statistics, MIT Press, vol. 92(2), pages 367-377, May.
    11. Angela J. Black & Olga Klinkowska & David G. McMillan & Fiona J. McMillan, 2014. "Forecasting Stock Returns: Do Commodity Prices Help?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(8), pages 627-639, December.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Ayedi Ahmed & Marjène Gana & Stéphane Goutte & Khaled Guesmi, 2023. "Managing Portfolio Risk During the BREXIT Crisis: A Cross-Quantilogram Analysis of Stock Markets and Commodities Across European Countries, the US, and BRICS," Working Papers halshs-04068651, HAL.
    2. Fernandez, Viviana & Pastén-Henríquez, Boris & Tapia-Griñen, Pablo & Wagner, Rodrigo, 2023. "Commodity prices under the threat of operational disruptions: Labor strikes at copper mines," Journal of Commodity Markets, Elsevier, vol. 32(C).
    3. Gkillas, Konstantinos & Konstantatos, Christoforos & Papathanasiou, Spyros & Wohar, Mark, 2023. "Estimation of value at risk for copper," Journal of Commodity Markets, Elsevier, vol. 32(C).
    4. Cheng Xin & Kailin Ji & Hao Chang & Yang Li & Ya-Qiong Liu, 2022. "Price Co-Movement between Electrical Equipment and Metal Commodities—A Time-Frequency Analysis," Sustainability, MDPI, vol. 14(20), pages 1-18, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Charles, Amelie & Darne, Olivier & Kim, Jae, 2016. "Stock Return Predictability: Evaluation based on Prediction Intervals," MPRA Paper 70143, University Library of Munich, Germany.
    2. Amélie Charles & Olivier Darné & Jae H. Kim, 2022. "Stock return predictability: Evaluation based on interval forecasts," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 363-385, April.
    3. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2019. "Structural instability and predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    4. Salisu, Afees A. & Isah, Kazeem O. & Raheem, Ibrahim D., 2019. "Testing the predictability of commodity prices in stock returns of G7 countries: Evidence from a new approach," Resources Policy, Elsevier, vol. 64(C).
    5. Narayan, Paresh Kumar & Narayan, Seema & Thuraisamy, Kannan Sivananthan, 2014. "Can institutions and macroeconomic factors predict stock returns in emerging markets?," Emerging Markets Review, Elsevier, vol. 19(C), pages 77-95.
    6. Afees A. Salisu & Kazeem Isah & Ibrahim D. Raheem, 2018. "Testing the predictability of commodity prices in stock returns: A new perspective," Working Papers 061, Centre for Econometric and Allied Research, University of Ibadan.
    7. Takuro Hidaka & Yuta Saito & Jun Sakamoto, 2021. "Historical Relationships and International Market Return Predictability: The Role of the UK in the Former British Colonies, Protectorates and Mandates," Discussion Papers in Economics and Business 21-08-Rev., Osaka University, Graduate School of Economics, revised Oct 2023.
    8. Salisu, Afees A. & Ademuyiwa, Idris & Isah, Kazeem O., 2018. "Revisiting the forecasting accuracy of Phillips curve: The role of oil price," Energy Economics, Elsevier, vol. 70(C), pages 334-356.
    9. repec:idn:journl:v:1:y:2019:i:sp2:p:1-12 is not listed on IDEAS
    10. Nima Nonejad, 2021. "Bayesian model averaging and the conditional volatility process: an application to predicting aggregate equity returns by conditioning on economic variables," Quantitative Finance, Taylor & Francis Journals, vol. 21(8), pages 1387-1411, August.
    11. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2015. "Stock return forecasting: Some new evidence," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 38-51.
    12. Afees A. Salisu & Abdulsalam Abidemi Sikiru, 2021. "Palm Oil Price–Exchange Rate Nexus In Indonesia And Malaysia," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 24(2), pages 169-180, June.
    13. Ma, Feng & Liu, Jing & Wahab, M.I.M. & Zhang, Yaojie, 2018. "Forecasting the aggregate oil price volatility in a data-rich environment," Economic Modelling, Elsevier, vol. 72(C), pages 320-332.
    14. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Tran, Vuong Thao, 2018. "Can economic policy uncertainty predict stock returns? Global evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 134-150.
    15. Nonejad, Nima, 2020. "Crude oil price volatility and equity return predictability: A comparative out-of-sample study," International Review of Financial Analysis, Elsevier, vol. 71(C).
    16. Salisu, Afees A. & Isah, Kazeem & Akanni, Lateef O., 2019. "Improving the predictability of stock returns with Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 857-867.
    17. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2015. "Are Indian stock returns predictable?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 506-531.
    18. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Westerlund, Joakim, 2016. "Are Islamic stock returns predictable? A global perspective," Pacific-Basin Finance Journal, Elsevier, vol. 40(PA), pages 210-223.
    19. Dinh Hoang Bach Phan & Thi Thao Nguyen Nguyen & Dat Thanh Nguyen, 2019. "A Study Of Indonesia’S Stock Market: How Predictable Is It?," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 21(12th BMEB), pages 465-476, January.
    20. Sharma, Susan Sunila, 2016. "Can consumer price index predict gold price returns?," Economic Modelling, Elsevier, vol. 55(C), pages 269-278.
    21. Westerlund, Joakim & Narayan, Paresh, 2016. "Testing for predictability in panels of any time series dimension," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1162-1177.

    More about this item

    Keywords

    Stock return predictability; Commodity returns; Four centuries;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • N2 - Economic History - - Financial Markets and Institutions
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

    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:finlet:v:40:y:2021:i:c:s1544612320307947. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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/frl .

    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.