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Stock market uncertainty and economic fundamentals: an entropy-based approach

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  • K. Ahn
  • D. Lee
  • S. Sohn
  • B. Yang

Abstract

This study investigates the effects of stock market uncertainty on economic fundamentals, represented by economic activities and systemic risk, in China. To capture the uncertainty in the Chinese stock market precisely, we use the entropy measure through symbolic time-series analysis. The empirical findings reveal strong spillover effects from stock market uncertainty to economic fundamentals. Specifically, an uncertainty shock generates (i) a short-term decline in industrial production, (ii) a rapid drop and rebound in the composite leading indicator, and (iii) an increase in systemic risk. To understand these findings, we suggest and validate the transmission channel through changes in consumption and investment.

Suggested Citation

  • K. Ahn & D. Lee & S. Sohn & B. Yang, 2019. "Stock market uncertainty and economic fundamentals: an entropy-based approach," Quantitative Finance, Taylor & Francis Journals, vol. 19(7), pages 1151-1163, July.
    • Handle: RePEc:taf:quantf:v:19:y:2019:i:7:p:1151-1163
    DOI: 10.1080/14697688.2019.1579922
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    Cited by:

    1. Andrey Shternshis & Piero Mazzarisi & Stefano Marmi, 2022. "Efficiency of the Moscow Stock Exchange before 2022," Papers 2207.10476, arXiv.org, revised Jul 2022.
    2. Andrey Shternshis & Stefano Marmi, 2023. "Price predictability at ultra-high frequency: Entropy-based randomness test," Papers 2312.16637, arXiv.org, revised Dec 2023.
    3. Bariviera, Aurelio F. & Font-Ferrer, Alejandro & Sorrosal-Forradellas, M. Teresa & Rosso, Osvaldo A., 2019. "An information theory perspective on the informational efficiency of gold price," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    4. Yi, Eojin & Ahn, Kwangwon & Choi, M.Y., 2022. "Cryptocurrency: Not far from equilibrium," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    5. Ma, Feng & Lu, Xinjie & Liu, Jia & Huang, Dengshi, 2022. "Macroeconomic attention and stock market return predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    6. Shternshis, Andrey & Mazzarisi, Piero & Marmi, Stefano, 2022. "Measuring market efficiency: The Shannon entropy of high-frequency financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    7. Jang, Hanwool & Song, Yena & Ahn, Kwangwon, 2020. "Can government stabilize the housing market? The evidence from South Korea," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    8. Lu, Xinjie & Ma, Feng & Wang, Tianyang & Wen, Fenghua, 2023. "International stock market volatility: A data-rich environment based on oil shocks," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 184-215.
    9. Yi, Eojin & Cho, Yerim & Sohn, Sungbin & Ahn, Kwangwon, 2021. "After the Splits: Information Flow between Bitcoin and Bitcoin Family," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    10. Ryu, Inug & Jang, Hanwool & Kim, Dongshin & Ahn, Kwangwon, 2021. "Market Efficiency of US REITs: A Revisit," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    11. Kleyton da Costa, 2023. "Anomaly Detection in Global Financial Markets with Graph Neural Networks and Nonextensive Entropy," Papers 2308.02914, arXiv.org, revised Aug 2023.
    12. Artem Stopochkin & Inessa Sytnik & Janusz Wielki & Nataliia Zemlianska, 2021. "Methodology for Building Trader's Investment Strategy Based on Assessment of the Market Value of the Company," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 913-935.

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