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Forecasting power of infectious diseases-related uncertainty for gold realized variance

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  • Bouri, Elie
  • Gkillas, Konstantinos
  • Gupta, Rangan
  • Pierdzioch, Christian

Abstract

We examine the forecasting power of a daily newspaper-based index of uncertainty associated with infectious diseases (EMVID) for gold market returns volatility via the heterogeneous autoregressive realized variance (HAR-RV) model. Our results show that the EMVID index increases realized variance (RV) at the highest level of statistical significance within-sample, while it improves the forecast accuracy of gold realized variance at short-, medium-, and long-run horizons in a statistically significant manner. Importantly, by assessing the role of this index during the recent pandemic, we find strong evidence for its critical role in forecasting gold RV. Such evidence has important portfolio implications for investors during the current period of unprecedented levels of uncertainty resulting from the outbreak of COVID-19.

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  • Bouri, Elie & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2021. "Forecasting power of infectious diseases-related uncertainty for gold realized variance," Finance Research Letters, Elsevier, vol. 42(C).
    • Handle: RePEc:eee:finlet:v:42:y:2021:i:c:s1544612321000179
    DOI: 10.1016/j.frl.2021.101936
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    References listed on IDEAS

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    1. Dirk G. Baur & Brian M. Lucey, 2010. "Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds and Gold," The Financial Review, Eastern Finance Association, vol. 45(2), pages 217-229, May.
    2. Gil-Alana, Luis A. & Aye, Goodness C. & Gupta, Rangan, 2015. "Trends and cycles in historical gold and silver prices," Journal of International Money and Finance, Elsevier, vol. 58(C), pages 98-109.
    3. Bonato, Matteo & Gupta, Rangan & Lau, Chi Keung Marco & Wang, Shixuan, 2020. "Moments-based spillovers across gold and oil markets," Energy Economics, Elsevier, vol. 89(C).
    4. Elie, Bouri & Naji, Jalkh & Dutta, Anupam & Uddin, Gazi Salah, 2019. "Gold and crude oil as safe-haven assets for clean energy stock indices: Blended copulas approach," Energy, Elsevier, vol. 178(C), pages 544-553.
    5. Bonato, Matteo & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2021. "A note on investor happiness and the predictability of realized volatility of gold," Finance Research Letters, Elsevier, vol. 39(C).
    6. Thiemo Fetzer & Lukas Hensel & Johannes Hermle & Christopher Roth, 2021. "Coronavirus Perceptions and Economic Anxiety," The Review of Economics and Statistics, MIT Press, vol. 103(5), pages 968–978-9, December.
    7. Baur, Dirk G. & McDermott, Thomas K., 2010. "Is gold a safe haven? International evidence," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1886-1898, August.
    8. Michael McAleer & Marcelo Medeiros, 2008. "Realized Volatility: A Review," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 10-45.
    9. Manabu Asai & Rangan Gupta & Michael McAleer, 2019. "The Impact of Jumps and Leverage in Forecasting the Co-Volatility of Oil and Gold Futures," Energies, MDPI, vol. 12(17), pages 1-17, September.
    10. John Y. Campbell, 2008. "Viewpoint: Estimating the equity premium," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 41(1), pages 1-21, February.
    11. 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.
    12. 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.
    13. Xiu, Dacheng, 2010. "Quasi-maximum likelihood estimation of volatility with high frequency data," Journal of Econometrics, Elsevier, vol. 159(1), pages 235-250, November.
    14. John Y. Campbell, 2007. "Estimating the Equity Premium," NBER Working Papers 13423, National Bureau of Economic Research, Inc.
    15. 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).
    16. Asai, Manabu & Gupta, Rangan & McAleer, Michael, 2020. "Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 933-948.
    17. Boubaker, Heni & Cunado, Juncal & Gil-Alana, Luis A. & Gupta, Rangan, 2020. "Global crises and gold as a safe haven: Evidence from over seven and a half centuries of data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    18. Demirer, Riza & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2019. "Time-varying risk aversion and realized gold volatility," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    19. Tiwari, Aviral Kumar & Aye, Goodness C. & Gupta, Rangan & Gkillas, Konstantinos, 2020. "Gold-oil dependence dynamics and the role of geopolitical risks: Evidence from a Markov-switching time-varying copula model," Energy Economics, Elsevier, vol. 88(C).
    20. Fang, Libing & Yu, Honghai & Xiao, Wen, 2018. "Forecasting gold futures market volatility using macroeconomic variables in the United States," Economic Modelling, Elsevier, vol. 72(C), pages 249-259.
    21. Wang, Xinya & Liu, Huifang & Huang, Shupei & Lucey, Brian, 2019. "Identifying the multiscale financial contagion in precious metal markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 209-219.
    22. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2016. "A boosting approach to forecasting the volatility of gold-price fluctuations under flexible loss," Resources Policy, Elsevier, vol. 47(C), pages 95-107.
    23. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    24. Hussain Shahzad, Syed Jawad & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav, 2020. "Safe haven, hedge and diversification for G7 stock markets: Gold versus bitcoin," Economic Modelling, Elsevier, vol. 87(C), pages 212-224.
    25. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
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    Cited by:

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    6. Castillo, Brenda & León, Ángel & Ñíguez, Trino-Manuel, 2021. "Backtesting VaR under the COVID-19 sudden changes in volatility," Finance Research Letters, Elsevier, vol. 43(C).
    7. Thanoj K. Muddana & Komal S.R. Bhimireddy & Anandamayee Majumdar & Rangan Gupta, 2024. "Forecasting Gold Returns Volatility Over 1258-2023: The Role of Moments," Working Papers 202421, University of Pretoria, Department of Economics.
    8. Gök, Remzi & Bouri, Elie & Gemici, Eray, 2022. "Can Twitter-based economic uncertainty predict safe-haven assets under all market conditions and investment horizons?," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    9. Al Rababa'a, Abdel Razzaq & Alomari, Mohammad & Mensi, Walid & Matar, Ali & Saidat, Zaid, 2021. "Does tracking the infectious diseases impact the gold, oil and US dollar returns and correlation? A quantile regression approach," Resources Policy, Elsevier, vol. 74(C).
    10. Celso-Arellano, Pedro & Gualajara, Victor & Coronado, Semei & Martinez, Jose N. & Venegas-Martínez, Francisco, 2023. "Impact of the global fear index (covid-19 panic) on the S&P global indices associated with natural resources, agribusiness, energy, metals and mining: Granger Causality and Shannon and Rényi Transfer ," MPRA Paper 117138, University Library of Munich, Germany, revised 06 Feb 2023.
    11. Shang, Yue & Wei, Yu & Chen, Yongfei, 2022. "Cryptocurrency policy uncertainty and gold return forecasting: A dynamic Occam's window approach," Finance Research Letters, Elsevier, vol. 50(C).
    12. Iyer, Subramanian Rama & Simkins, Betty J., 2022. "COVID-19 and the Economy: Summary of research and future directions," Finance Research Letters, Elsevier, vol. 47(PB).
    13. Dash, Saumya Ranjan & Maitra, Debasish, 2022. "The COVID-19 pandemic uncertainty, investor sentiment, and global equity markets: Evidence from the time-frequency co-movements," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    14. Imran Yousaf & Vasilios Plakandaras & Elie Bouri & Rangan Gupta, 2022. "Hedge and Safe Haven Properties of Gold, US Treasury, Bitcoin, and Dollar/CHF against the FAANA Companies and S&P 500," Working Papers 202227, University of Pretoria, Department of Economics.
    15. Yousaf, Imran & Plakandaras, Vasilios & Bouri, Elie & Gupta, Rangan, 2023. "Hedge and safe-haven properties of FAANA against gold, US Treasury, bitcoin, and US Dollar/CHF during the pandemic period," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    16. Esam Mahdi & Ameena Al-Abdulla, 2022. "Impact of COVID-19 Pandemic News on the Cryptocurrency Market and Gold Returns: A Quantile-on-Quantile Regression Analysis," Econometrics, MDPI, vol. 10(2), pages 1-14, June.
    17. Tamilselvan, M. & Halder, Abhishek & Kannadhasan, M., 2024. "Exploring the ingredients, mixtures, and inclinations of geopolitical risk," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 187-206.
    18. Mo, Bin & Nie, He & Zhao, Rongjie, 2024. "Dynamic nonlinear effects of geopolitical risks on commodities: Fresh evidence from quantile methods," Energy, Elsevier, vol. 288(C).
    19. Ştefan Cristian Gherghina & Liliana Nicoleta Simionescu, 2023. "Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-58, December.
    20. Bouri, Elie & Gupta, Rangan & Nel, Jacobus & Shiba, Sisa, 2022. "Contagious diseases and gold: Over 700 years of evidence from quantile regressions," Finance Research Letters, Elsevier, vol. 50(C).
    21. Konstantinos Gkillas & Christoforos Konstantatos & Costas Siriopoulos, 2021. "Uncertainty Due to Infectious Diseases and Stock–Bond Correlation," Econometrics, MDPI, vol. 9(2), pages 1-18, April.
    22. Dutta, Anupam & Park, Donghyun & Uddin, Gazi Salah & Kanjilal, Kakali & Ghosh, Sajal, 2024. "Do dirty and clean energy investments react to infectious disease-induced uncertainty?," Technological Forecasting and Social Change, Elsevier, vol. 205(C).

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    More about this item

    Keywords

    Uncertainty; Infectious diseases; COVID-19; Gold; Realized variance; 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

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