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Predictability of the Realised Volatility of International Stock Markets Amid Uncertainty Related to Infectious Diseases

Author

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  • Sisa Shiba

    (Department of Economics, University of Pretoria, Pretoria 0002, South Africa)

  • Juncal Cunado

    (Department of Economics, University of Navarra, 20280 Pamplona, Spain)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria 0002, South Africa)

Abstract

In the context of the great turmoil in the financial markets caused by the COVID-19 pandemic, the predictability of daily infectious diseases-related uncertainty (EMVID) for international stock markets volatilities is examined using heterogeneous autoregressive realised variance (HAR-RV) models. A recursive estimation approach in the short-, medium- and long-run out-of-sample predictability is considered and the main findings show that the EMVID index plays a significant role in forecasting the volatility of international stock markets. Furthermore, the results suggest that the most vulnerable stock markets to EMVID are those in Singapore, Portugal and The Netherlands. The implications of these results for investors and portfolio managers amid high levels of uncertainty resulting from infectious diseases are discussed.

Suggested Citation

  • Sisa Shiba & Juncal Cunado & Rangan Gupta, 2022. "Predictability of the Realised Volatility of International Stock Markets Amid Uncertainty Related to Infectious Diseases," JRFM, MDPI, vol. 15(1), pages 1-18, January.
    • Handle: RePEc:gam:jjrfmx:v:15:y:2022:i:1:p:18-:d:717834
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    References listed on IDEAS

    as
    1. Gupta, Rangan & Subramaniam, Sowmya & Bouri, Elie & Ji, Qiang, 2021. "Infectious disease-related uncertainty and the safe-haven characteristic of US treasury securities," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 289-298.
    2. Al-Awadhi, Abdullah M. & Alsaifi, Khaled & Al-Awadhi, Ahmad & Alhammadi, Salah, 2020. "Death and contagious infectious diseases: Impact of the COVID-19 virus on stock market returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    3. Chen, Yufeng & Li, Wenqi & Qu, Fang, 2019. "Dynamic asymmetric spillovers and volatility interdependence on China’s stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 825-838.
    4. Scott R. Baker & Nicholas Bloom & Steven J. Davis & Stephen J. Terry, 2020. "COVID-Induced Economic Uncertainty," NBER Working Papers 26983, National Bureau of Economic Research, Inc.
    5. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    6. Juncal Cunado & David Gabauer & Rangan Gupta, 2024. "Realized volatility spillovers between energy and metal markets: a time-varying connectedness approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-17, December.
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    Cited by:

    1. Guo, Changrong & Zhang, Xiangyu & Raza, Syed Ali & Masood, Amna, 2024. "Asymmetrical connectedness between infectious diseases-related equity market volatility and prices of precious metals," Resources Policy, Elsevier, vol. 88(C).

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    More about this item

    Keywords

    uncertainty; infectious diseases; COVID-19; international stock markets; realised volatility; forecasting;
    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
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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