IDEAS home Printed from https://ideas.repec.org/a/eee/beexfi/v27y2020ics2214635020302136.html
   My bibliography  Save this article

The COVID-19 global fear index and the predictability of commodity price returns

Author

Listed:
  • Salisu, Afees A.
  • Akanni, Lateef
  • Raheem, Ibrahim

Abstract

In this paper, we subject the global fear index (GFI) for the COVID-19 pandemic to empirical scrutiny by examining its predictive power in the predictability of commodity price returns during the pandemic. One of the attractions to the index lies in its coverage as all the countries and by extension regions and territories in the world are considered in the construction of the index. Our results show evidence of a positive relationship between commodity price returns and the global fear index, confirming that commodity returns increase as COVID-19 related fear rises. By way of extension, we further establish that commodity market offers better safe-haven properties than the stock market given the negative association between GFI and the latter. Finally, the GFI series improves the forecast accuracy of the predictive model for commodity price returns and its forecast outcome outperforms the historical average (constant returns) model both for the in-sample and out-of-sample forecasts. Our results are robust to alternative measures of pandemics.

Suggested Citation

  • Salisu, Afees A. & Akanni, Lateef & Raheem, Ibrahim, 2020. "The COVID-19 global fear index and the predictability of commodity price returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    • Handle: RePEc:eee:beexfi:v:27:y:2020:i:c:s2214635020302136
    DOI: 10.1016/j.jbef.2020.100383
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S2214635020302136
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jbef.2020.100383?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
    ---><---

    References listed on IDEAS

    as
    1. Zhang, Jilin & Lai, Yongzeng & Lin, Jianghong, 2017. "The day-of-the-Week effects of stock markets in different countries," Finance Research Letters, Elsevier, vol. 20(C), pages 47-62.
    2. Ing-Haw Cheng & Wei Xiong, 2014. "Financialization of Commodity Markets," Annual Review of Financial Economics, Annual Reviews, vol. 6(1), pages 419-441, December.
    3. Tule, Moses K. & Salisu, Afees A. & Chiemeke, Charles C., 2019. "Can agricultural commodity prices predict Nigeria's inflation?," Journal of Commodity Markets, Elsevier, vol. 16(C).
    4. Salisu, Afees A. & Ndako, Umar B., 2018. "Modelling stock price–exchange rate nexus in OECD countries: A new perspective," Economic Modelling, Elsevier, vol. 74(C), pages 105-123.
    5. 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.
    6. Donia Aloui & Stéphane Goutte & Khaled Guesmi & Rafla Hchaichi, 2020. "COVID 19's impact on crude oil and natural gas S&P GS Indexes," Working Papers halshs-02613280, HAL.
    7. Corbet, Shaen & Larkin, Charles & Lucey, Brian, 2020. "The contagion effects of the COVID-19 pandemic: Evidence from gold and cryptocurrencies," Finance Research Letters, Elsevier, vol. 35(C).
    8. Salisu, Afees A. & Raheem, Ibrahim D. & Ndako, Umar B., 2020. "The inflation hedging properties of gold, stocks and real estate: A comparative analysis," Resources Policy, Elsevier, vol. 66(C).
    9. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    10. Chen, Yu-chin & Turnovsky, Stephen J. & Zivot, Eric, 2014. "Forecasting inflation using commodity price aggregates," Journal of Econometrics, Elsevier, vol. 183(1), pages 117-134.
    11. Salisu, Afees A. & Isah, Kazeem O., 2017. "Revisiting the oil price and stock market nexus: A nonlinear Panel ARDL approach," Economic Modelling, Elsevier, vol. 66(C), pages 258-271.
    12. Jan Ditzen, 2018. "Estimating dynamic common-correlated effects in Stata," Stata Journal, StataCorp LP, vol. 18(3), pages 585-617, September.
    13. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    14. Chudik, Alexander & Pesaran, M. Hashem, 2015. "Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors," Journal of Econometrics, Elsevier, vol. 188(2), pages 393-420.
    15. Afees A. Salisu & Lateef O. Akanni, 2020. "Constructing a Global Fear Index for the COVID-19 Pandemic," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(10), pages 2310-2331, August.
    16. Sharif, Arshian & Aloui, Chaker & Yarovaya, Larisa, 2020. "COVID-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet-based approach," International Review of Financial Analysis, Elsevier, vol. 70(C).
    17. Conlon, Thomas & McGee, Richard, 2020. "Safe haven or risky hazard? Bitcoin during the Covid-19 bear market," Finance Research Letters, Elsevier, vol. 35(C).
    18. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    19. Markus Eberhardt, 2012. "Estimating panel time-series models with heterogeneous slopes," Stata Journal, StataCorp LP, vol. 12(1), pages 61-71, March.
    20. Wang, Jian & Shao, Wei & Kim, Junseok, 2020. "Analysis of the impact of COVID-19 on the correlations between crude oil and agricultural futures," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    21. Robertson, D & Symons, J, 1992. "Some Strange Properties of Panel Data Estimators," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(2), pages 175-189, April-Jun.
    22. Salisu, Afees A. & Ebuh, Godday U. & Usman, Nuruddeen, 2020. "Revisiting oil-stock nexus during COVID-19 pandemic: Some preliminary results," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 280-294.
    23. Hamilton, James D. & Wu, Jing Cynthia, 2014. "Risk premia in crude oil futures prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 9-37.
    24. Arnold, Stephan & Auer, Benjamin R., 2015. "What do scientists know about inflation hedging?," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 187-214.
    25. Scott R. Baker & Nicholas Bloom & Steven J. Davis & Kyle J. Kost & Marco C. Sammon & Tasaneeya Viratyosin, 2020. "The Unprecedented Stock Market Impact of COVID-19," NBER Working Papers 26945, National Bureau of Economic Research, Inc.
    26. Chen, Yu-chin & Rogoff, Kenneth, 2003. "Commodity currencies," Journal of International Economics, Elsevier, vol. 60(1), pages 133-160, May.
    27. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2017. "Oil shocks and stock markets: Dynamic connectedness under the prism of recent geopolitical and economic unrest," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 1-26.
    28. 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.
    Full references (including those not matched with items on IDEAS)

    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. Salisu, Afees A. & Vo, Xuan Vinh, 2021. "Firm-specific news and the predictability of Consumer stocks in Vietnam," Finance Research Letters, Elsevier, vol. 41(C).
    2. Afees A. Salisu & Ibrahim D. Raheem & Godstime O. Eigbiremolen, 2022. "The behaviour of U.S. stocks to financial and health risks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4607-4618, October.
    3. Afees A. Salisu & Elias A. Udeaja & Silva Opuala-Charles, 2022. "Central Bank Independence And Price Stability Under Alternative Political Regimes: A Global Evidence," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 25(2), pages 155-172, August.
    4. Salisu, Afees A. & Vo, Xuan Vinh, 2020. "Predicting stock returns in the presence of COVID-19 pandemic: The role of health news," International Review of Financial Analysis, Elsevier, vol. 71(C).
    5. Olubusoye, Olusanya E & Yaya, OlaOluwa S. & Ogbonna, Ahamuefula, 2021. "An Information-Based Index of Uncertainty and the predictability of Energy Prices," MPRA Paper 109839, University Library of Munich, Germany.
    6. Afees A. Salisu & Ahamuefula E. Ogbonna & Tirimisiyu F. Oloko & Idris A. Adediran, 2021. "A New Index for Measuring Uncertainty Due to the COVID-19 Pandemic," Sustainability, MDPI, vol. 13(6), pages 1-18, March.
    7. Ding, Hui & Huang, Yisu & Wang, Jiqian, 2023. "Have the predictability of oil changed during the COVID-19 pandemic: Evidence from international stock markets," International Review of Financial Analysis, Elsevier, vol. 87(C).
    8. Afees A. Salisu & Abdulsalam Abidemi Sikiru & Philip C. Omoke, 2023. "COVID-19 pandemic and financial innovations," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3885-3904, August.
    9. Salisu, Afees A. & Ndako, Umar B. & Oloko, Tirimisiyu F., 2019. "Assessing the inflation hedging of gold and palladium in OECD countries," Resources Policy, Elsevier, vol. 62(C), pages 357-377.
    10. Ghaemi Asl, Mahdi & Adekoya, Oluwasegun Babatunde & Rashidi, Muhammad Mahdi & Ghasemi Doudkanlou, Mohammad & Dolatabadi, Ali, 2022. "Forecast of Bayesian-based dynamic connectedness between oil market and Islamic stock indices of Islamic oil-exporting countries: Application of the cascade-forward backpropagation network," Resources Policy, Elsevier, vol. 77(C).
    11. Demiralay, Sercan & Gencer, Hatice Gaye & Bayraci, Selcuk, 2021. "How do Artificial Intelligence and Robotics Stocks co-move with traditional and alternative assets in the age of the 4th industrial revolution? Implications and Insights for the COVID-19 period," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    12. Raheem, Ibrahim D., 2021. "COVID-19 pandemic and the safe haven property of Bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 370-375.
    13. Salisu, Afees A. & Shaik, Muneer, 2022. "Islamic Stock indices and COVID-19 pandemic," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 282-293.
    14. Gangopadhyay, Partha & Jain, Siddharth & Bakry, Walid, 2022. "In search of a rational foundation for the massive IT boom in the Australian banking industry: Can the IT boom really drive relationship banking?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    15. Salisu, Afees A. & Raheem, Ibrahim D. & Vo, Xuan Vinh, 2021. "Assessing the safe haven property of the gold market during COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 74(C).
    16. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    17. Salisu, Afees A. & Vo, Xuan Vinh & Lucey, Brian, 2021. "Gold and US sectoral stocks during COVID-19 pandemic," Research in International Business and Finance, Elsevier, vol. 57(C).
    18. Tong, Yuan & Wan, Ning & Dai, Xingyu & Bi, Xiaoyi & Wang, Qunwei, 2022. "China's energy stock market jumps: To what extent does the COVID-19 pandemic play a part?," Energy Economics, Elsevier, vol. 109(C).
    19. Padhan, Rakesh & Prabheesh, K.P., 2021. "The economics of COVID-19 pandemic: A survey," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 220-237.
    20. Yarovaya, Larisa & Brzeszczyński, Janusz & Goodell, John W. & Lucey, Brian & Lau, Chi Keung Marco, 2022. "Rethinking financial contagion: Information transmission mechanism during the COVID-19 pandemic," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).

    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:beexfi:v:27:y:2020:i:c:s2214635020302136. 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: https://www.journals.elsevier.com/journal-of-behavioral-and-experimental-finance .

    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.