IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v32y2020ics1544612318305609.html
   My bibliography  Save this article

The impact of Baidu Index sentiment on the volatility of China's stock markets

Author

Listed:
  • Fang, Jianchun
  • Gozgor, Giray
  • Lau, Chi-Keung Marco
  • Lu, Zhou

Abstract

This paper examines the relationship between investor sentiment and the volatility of China's stock markets. We use the data from Baidu, China's leading search engine, for information on investor sentiment. In two different Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models, the baseline model and the Baidu-Index extended model, we forecast the return volatility of China's stock markets. We find that the Baidu-Index extended model performs better than the baseline model. This paper shows that the search volume of relevant key words from Baidu Index improves volatility forecasting of China's stock markets.

Suggested Citation

  • Fang, Jianchun & Gozgor, Giray & Lau, Chi-Keung Marco & Lu, Zhou, 2020. "The impact of Baidu Index sentiment on the volatility of China's stock markets," Finance Research Letters, Elsevier, vol. 32(C).
    • Handle: RePEc:eee:finlet:v:32:y:2020:i:c:s1544612318305609
    DOI: 10.1016/j.frl.2019.01.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612318305609
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2019.01.011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Huina Mao & Scott Counts & Johan Bollen, 2011. "Predicting Financial Markets: Comparing Survey, News, Twitter and Search Engine Data," Papers 1112.1051, arXiv.org.
    2. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    3. Bijl, Laurens & Kringhaug, Glenn & Molnár, Peter & Sandvik, Eirik, 2016. "Google searches and stock returns," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 150-156.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. 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.
    6. Karim Rochdi & Marian Dietzel, 2015. "Outperforming the benchmark: online information demand and REIT market performance," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 33(2), pages 169-195, March.
    7. Ackert, Lucy F. & Jiang, Lei & Lee, Hoan Soo & Liu, Jie, 2016. "Influential investors in online stock forums," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 39-46.
    8. 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.
    9. Abugri, Benjamin A., 2008. "Empirical relationship between macroeconomic volatility and stock returns: Evidence from Latin American markets," International Review of Financial Analysis, Elsevier, vol. 17(2), pages 396-410.
    10. Massimiliano Caporin & Francesco Poli, 2017. "Building News Measures from Textual Data and an Application to Volatility Forecasting," Econometrics, MDPI, vol. 5(3), pages 1-46, August.
    11. Pyo, Dong-Jin, 2017. "Can Big Data Help Predict Financial Market Dynamics?: Evidence from the Korean Stock Market," East Asian Economic Review, Korea Institute for International Economic Policy, vol. 21(2), pages 147-165, June.
    12. Dastgir, Shabbir & Demir, Ender & Downing, Gareth & Gozgor, Giray & Lau, Chi Keung Marco, 2019. "The causal relationship between Bitcoin attention and Bitcoin returns: Evidence from the Copula-based Granger causality test," Finance Research Letters, Elsevier, vol. 28(C), pages 160-164.
    13. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    14. Kasman, Saadet & Vardar, Gülin & Tunç, Gökçe, 2011. "The impact of interest rate and exchange rate volatility on banks' stock returns and volatility: Evidence from Turkey," Economic Modelling, Elsevier, vol. 28(3), pages 1328-1334, May.
    15. Raphael H Heiberger, 2015. "Collective Attention and Stock Prices: Evidence from Google Trends Data on Standard and Poor's 100," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-14, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Anastasiou, Dimitris & Ballis, Antonis & Drakos, Konstantinos, 2022. "Constructing a positive sentiment index for COVID-19: Evidence from G20 stock markets," International Review of Financial Analysis, Elsevier, vol. 81(C).
    2. Chaiyuth Padungsaksawasdi & Sirimon Treepongkaruna & Robert Brooks, 2019. "Investor Attention and Stock Market Activities: New Evidence from Panel Data," IJFS, MDPI, vol. 7(2), pages 1-19, June.
    3. Alomari, Mohammad & Al Rababa’a, Abdel Razzaq & El-Nader, Ghaith & Alkhataybeh, Ahmad & Ur Rehman, Mobeen, 2021. "Examining the effects of news and media sentiments on volatility and correlation: Evidence from the UK," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 280-297.
    4. Aleksandra Rutkowska & Agata Kliber, 2021. "Say anything you want about me if you spell my name right: the effect of Internet searches on financial market," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 633-664, June.
    5. Zhou, Siwen, 2018. "Exploring the Driving Forces of the Bitcoin Exchange Rate Dynamics: An EGARCH Approach," MPRA Paper 89445, University Library of Munich, Germany.
    6. Salisu, Afees A. & Vo, Xuan Vinh, 2021. "Firm-specific news and the predictability of Consumer stocks in Vietnam," Finance Research Letters, Elsevier, vol. 41(C).
    7. Xiong, Xiong & Meng, Yongqiang & Joseph, Nathan Lael & Shen, Dehua, 2020. "Stock mispricing, hard-to-value stocks and the influence of internet stock message boards," International Review of Financial Analysis, Elsevier, vol. 72(C).
    8. Lyócsa, Štefan & Halousková, Martina & Haugom, Erik, 2023. "The US banking crisis in 2023: Intraday attention and price variation of banks at risk," Finance Research Letters, Elsevier, vol. 57(C).
    9. Thomas Dimpfl & Vladislav Kleiman, 2019. "Investor Pessimism and the German Stock Market: Exploring Google Search Queries," German Economic Review, Verein für Socialpolitik, vol. 20(1), pages 1-28, February.
    10. Salisu, Afees A. & Ogbonna, Ahamuefula E., 2022. "The return volatility of cryptocurrencies during the COVID-19 pandemic: Assessing the news effect," Global Finance Journal, Elsevier, vol. 54(C).
    11. Christophe Desagre & Catherine D'Hondt, 2020. "Googlization and retail investors' trading activity," LIDAM Discussion Papers LFIN 2020004, Université catholique de Louvain, Louvain Finance (LFIN).
    12. Duc Dang Thi Viet & Hoai Nguyen Thu & Nguyen Van Phuoc & Nguyen Dang Phong & Anh Nguyen Huong & Hai Ho Hong, 2024. "Google Search intensity and stock returns in frontier markets: Evidence from the Vietnamese market," Economics and Business Review, Sciendo, vol. 10(1), pages 30-56, April.
    13. Raúl Gómez‐Martínez & Carmen Orden‐Cruz & Juan Gabriel Martínez‐Navalón, 2022. "Wikipedia pageviews as investors’ attention indicator for Nasdaq," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 29(1), pages 41-49, January.
    14. Aouadi, Amal & Arouri, Mohamed & Teulon, Frédéric, 2013. "Investor attention and stock market activity: Evidence from France," Economic Modelling, Elsevier, vol. 35(C), pages 674-681.
    15. Kim, Neri & Lučivjanská, Katarína & Molnár, Peter & Villa, Roviel, 2019. "Google searches and stock market activity: Evidence from Norway," Finance Research Letters, Elsevier, vol. 28(C), pages 208-220.
    16. López-Cabarcos, M. Ángeles & Pérez-Pico, Ada M. & Piñeiro-Chousa, Juan & Šević, Aleksandar, 2021. "Bitcoin volatility, stock market and investor sentiment. Are they connected?," Finance Research Letters, Elsevier, vol. 38(C).
    17. Chen, Rongda & Wu, Ling & Jin, Chenglu & Wang, Shengnan, 2021. "Unintended investor sentiment on bank financial products: Evidence from China," Emerging Markets Review, Elsevier, vol. 49(C).
    18. Semen Son-Turan, 2016. "The Impact of Investor Sentiment on the "Leverage Effect"," International Econometric Review (IER), Econometric Research Association, vol. 8(1), pages 4-18, April.
    19. Swamy, Vighneswara & Dharani, M. & Takeda, Fumiko, 2019. "Investor attention and Google Search Volume Index: Evidence from an emerging market using quantile regression analysis," Research in International Business and Finance, Elsevier, vol. 50(C), pages 1-17.
    20. Tihana Škrinjarić, 2019. "Time Varying Spillovers between the Online Search Volume and Stock Returns: Case of CESEE Markets," IJFS, MDPI, vol. 7(4), pages 1-30, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:32:y:2020:i:c:s1544612318305609. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.