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Volatility persistence and asymmetry under the microscope: the role of information demand for gold and oil

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  • Georgios Bampinas
  • Theodore Panagiotidis
  • Christina Rouska

Abstract

This study explores the relationship between Google search activity and the conditional volatility of oil and gold spot market returns. By aggregating the volume of queries related to the two commodity markets in the spirit of Da et al. (), we construct a weekly Searching Volume Index (SVI) for each market as proxy of households and investors information demand. We employ a rolling EGARCH framework to reveal how the significance of information demand has evolved through time. We find that higher information demand increases conditional volatility in gold and oil spot market returns. Information flows from Google SVI's reduce the proportion of the significant volatility asymmetry produced by negative shocks in both commodity markets. The latter is more profound in the gold market.

Suggested Citation

  • Georgios Bampinas & Theodore Panagiotidis & Christina Rouska, 2019. "Volatility persistence and asymmetry under the microscope: the role of information demand for gold and oil," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 180-197, February.
    • Handle: RePEc:bla:scotjp:v:66:y:2019:i:1:p:180-197
    DOI: 10.1111/sjpe.12177
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    Cited by:

    1. Ramos, Sofia B. & Latoeiro, Pedro & Veiga, Helena, 2020. "Limited attention, salience of information and stock market activity," Economic Modelling, Elsevier, vol. 87(C), pages 92-108.
    2. Tsai, I-Chun & Chen, Han-Bo & Lin, Che-Chun, 2024. "The ability of energy commodities to hedge the dynamic risk of epidemic black swans," Resources Policy, Elsevier, vol. 89(C).
    3. Tanin, Tauhidul Islam & Sarker, Ashutosh & Hammoudeh, Shawkat & Shahbaz, Muhammad, 2021. "Do volatility indices diminish gold's appeal as a safe haven to investors before and during the COVID-19 pandemic?," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 214-235.
    4. Bernardina Algieri, 2021. "Fast & furious: Do psychological and legal factors affect commodity price volatility?," The World Economy, Wiley Blackwell, vol. 44(4), pages 980-1017, April.
    5. Bernardina Algieri & Matthias Kalkuhl, 2019. "Efficiency and Forecast Performance of Commodity Futures Markets," American Journal of Economics and Business Administration, Science Publications, vol. 11(1), pages 19-34, June.
    6. Gaies, Brahim & Nakhli, Mohamed Sahbi & Sahut, Jean-Michel & Schweizer, Denis, 2023. "Interactions between investors’ fear and greed sentiment and Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    7. Marcos González-Fernández & Carmen González-Velasco, 2019. "An approach to predict Spanish mortgage market activity using Google data," Economics and Business Letters, Oviedo University Press, vol. 8(4), pages 209-214.
    8. Li, Sufang & Xu, Qiufan & Lv, Yixue & Yuan, Di, 2022. "Public attention, oil and gold markets during the COVID-19: Evidence from time-frequency analysis," Resources Policy, Elsevier, vol. 78(C).
    9. Spyridon Boikos & Eirini Makantasi & Theodore Panagiotidis, 2023. "Macroeconomic Uncertainty Indices for European Countries," Notas Económicas, Faculty of Economics, University of Coimbra, issue 57, pages 7-56, December.
    10. González-Fernández, Marcos & González-Velasco, Carmen, 2020. "A sentiment index to measure sovereign risk using Google data," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 406-418.
    11. Joscha Beckmann & Robert L. Czudaj & Gary Koop, 2019. "An empirical assessment of recent challenges in today's financial markets," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 1-4, February.

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