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Forecastability of Agricultural Commodity Futures Realised Volatility with Daily Infectious Disease-Related Uncertainty

Author

Listed:
  • Sisa Shiba

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Goodness C. Aye

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Samrat Goswami

    (Department of Rural Studies, Tripura University, Agartala 799022, Tripura, India)

Abstract

Given the food supply chain disruption from COVID-19 lockdowns around the world, we examine the predictive power of daily infectious diseases-related uncertainty (EMVID) on commodity traded futures within the agricultural bracket, sometimes known as the softs, using the heterogeneous autoregressive realised variance (HAR-RV) model. Considering the short-, medium-, and long-run recursive out-of-sample estimation approach, we estimate daily realised volatility by using intraday data within the 5 min interval for 15 agricultural commodity futures. During the COVID-19 episode, our results indicated that EMVID plays an important role in predicting the future path of agricultural commodity traded futures in the short, medium, and long run, i.e., h = 1, 5, and 22, respectively. According to the MSE-F test, these results are statistically significant. These results contain important implications for investors, portfolio managers, and speculators when faced with investment risk management and strategic asset allocation during infectious disease-related uncertainty.

Suggested Citation

  • Sisa Shiba & Goodness C. Aye & Rangan Gupta & Samrat Goswami, 2022. "Forecastability of Agricultural Commodity Futures Realised Volatility with Daily Infectious Disease-Related Uncertainty," JRFM, MDPI, vol. 15(11), pages 1-15, November.
    • Handle: RePEc:gam:jjrfmx:v:15:y:2022:i:11:p:525-:d:968525
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    References listed on IDEAS

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    1. 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).
    2. O'Hara, Sabine & Toussaint, Etienne C., 2021. "Food access in crisis: Food security and COVID-19," Ecological Economics, Elsevier, vol. 180(C).
    3. Zhang, Wenting & Hamori, Shigeyuki, 2021. "Crude oil market and stock markets during the COVID-19 pandemic: Evidence from the US, Japan, and Germany," International Review of Financial Analysis, Elsevier, vol. 74(C).
    4. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2020. "Forecasting realized gold volatility: Is there a role of geopolitical risks?," Finance Research Letters, Elsevier, vol. 35(C).
    5. Maretno Agus Harjoto & Fabrizio Rossi & John K. Paglia, 2021. "COVID-19: stock market reactions to the shock and the stimulus," Applied Economics Letters, Taylor & Francis Journals, vol. 28(10), pages 795-801, June.
    6. 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).
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    Cited by:

    1. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2023. "Financial Stress and Realized Volatility: The Case of Agricultural Commodities," Working Papers 202320, University of Pretoria, Department of Economics.

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    More about this item

    Keywords

    commodity futures; infectious disease-related uncertainty; forecasting; realised volatility;
    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
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

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