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Retail investor attention and stock market behavior in Russia-Ukraine conflict based on Chinese practices: Evidence from transfer entropy causal network

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  • Jin, Xiu
  • Xue, Qiuyang

Abstract

From the non-linear information transmission angle, we look into the interactions between retail investor attention and the stock market before and during the Russia-Ukraine conflict. We construct transfer entropy causal networks between retail investor attention and stock market behavior on three counts: return, trading volume and volatility. We discover that bi-directional causal relations exist between investor attention and the stock market. We also find that after the conflict outbreak, retail investor attention becomes more influential on return, trading volume and volatility. The stock market return and volatility have more impact on investor attention. Information transfer efficiency increases after the outbreak.

Suggested Citation

  • Jin, Xiu & Xue, Qiuyang, 2023. "Retail investor attention and stock market behavior in Russia-Ukraine conflict based on Chinese practices: Evidence from transfer entropy causal network," Finance Research Letters, Elsevier, vol. 58(PB).
    • Handle: RePEc:eee:finlet:v:58:y:2023:i:pb:s1544612323008292
    DOI: 10.1016/j.frl.2023.104457
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    1. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    2. Nartea, Gilbert V. & Kong, Dongmin & Wu, Ji, 2017. "Do extreme returns matter in emerging markets? Evidence from the Chinese stock market," Journal of Banking & Finance, Elsevier, vol. 76(C), pages 189-197.
    3. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    4. Xing, Xiaoyun & Xu, Zihan & Chen, Ying & Ouyang, WenPei & Deng, Jing & Pan, Huanxue, 2023. "The impact of the Russia–Ukraine conflict on the energy subsector stocks in China: A network-based approach," Finance Research Letters, Elsevier, vol. 53(C).
    5. Li, Sufang & Zhang, Hu & Yuan, Di, 2019. "Investor attention and crude oil prices: Evidence from nonlinear Granger causality tests," Energy Economics, Elsevier, vol. 84(C).
    6. García-Medina, Andrés & Sandoval, Leonidas & Bañuelos, Efraín Urrutia & Martínez-Argüello, A.M., 2018. "Correlations and flow of information between the New York Times and stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 403-415.
    7. Martina Halouskov'a & Daniel Stav{s}ek & Mat'uv{s} Horv'ath, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Papers 2205.05985, arXiv.org, revised Aug 2022.
    8. Thomas Dimpfl & Stephan Jank, 2016. "Can Internet Search Queries Help to Predict Stock Market Volatility?," European Financial Management, European Financial Management Association, vol. 22(2), pages 171-192, March.
    9. Matthias Bank & Martin Larch & Georg Peter, 2011. "Google search volume and its influence on liquidity and returns of German stocks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(3), pages 239-264, September.
    10. Niu, Hongli & Hu, Ziang, 2021. "Information transmission and entropy-based network between Chinese stock market and commodity futures market," Resources Policy, Elsevier, vol. 74(C).
    11. Benhmad, François, 2012. "Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach," Economic Modelling, Elsevier, vol. 29(4), pages 1505-1514.
    12. Tantaopas, Parkpoom & Padungsaksawasdi, Chaiyuth & Treepongkaruna, Sirimon, 2016. "Attention effect via internet search intensity in Asia-Pacific stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 38(C), pages 107-124.
    13. Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.
    14. Ferreira, Paulo & Almeida, Dora & Dionísio, Andreia & Bouri, Elie & Quintino, Derick, 2022. "Energy markets – Who are the influencers?," Energy, Elsevier, vol. 239(PA).
    15. Anjan V. Thakor, 2015. "The Financial Crisis of 2007–2009: Why Did It Happen and What Did We Learn?," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 4(2), pages 155-205.
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    Cited by:

    1. Gao, Wang & Zhang, Hongwei, 2024. "The role of education attention on high-tech markets in an emerging economy: Evidence from QQR and NCQ techniques," Technological Forecasting and Social Change, Elsevier, vol. 207(C).

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