IDEAS home Printed from https://ideas.repec.org/a/bpj/germec/v20y2019i1p1-28.html

Investor Pessimism and the German Stock Market: Exploring Google Search Queries

Author

Listed:
  • Dimpfl Thomas

    (University of Tübingen,Tübingen, Germany)

  • Kleiman Vladislav

    (University of Tübingen,Tübingen, Germany)

Abstract

We analyze the relationship of retail investor sentiment and the German stock market by introducing four distinct investor pessimism indices (IPIs) based on selected aggregate Google search queries. We assess the predictive power of weekly changes in sentiment captured by the IPIs for contemporaneous and future DAX returns, volatility and trading volume. The indices are found to have individually varying, but overall remarkably high explanatory power. An increase in retail investor pessimism is accompanied by decreasing contemporaneous market returns and an increase in volatility and trading volume. Future returns tend to increase while future volatility and trading volume decrease. The outcome is in line with the conjecture of correction effects. Overall, the results are well in line with modern investor sentiment theory.

Suggested Citation

  • Dimpfl Thomas & Kleiman Vladislav, 2019. "Investor Pessimism and the German Stock Market: Exploring Google Search Queries," German Economic Review, De Gruyter, vol. 20(1), pages 1-28, February.
    • Handle: RePEc:bpj:germec:v:20:y:2019:i:1:p:1-28
    DOI: 10.1111/geer.12137
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/geer.12137
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1111/geer.12137?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 look for a different version below or

    for a different version of it.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tamara Teplova & Maksim Fayzulin, 2025. "Decoding Russian stock market trends through ensemble methods and sentiment analysis of social media," Annals of Operations Research, Springer, vol. 353(3), pages 1123-1172, October.
    2. Ming‐Hung Wu & Wei‐Che Tsai & Pei‐Shih Weng & Dan‐Yi Li, 2021. "Effects of investor attention in China's commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(8), pages 1315-1332, August.
    3. Müller, Karsten, 2020. "German forecasters' narratives: How informative are German business cycle forecast reports?," Working Papers 23, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    4. Desagre, Christophe & D’Hondt, Catherine, 2021. "Googlization and retail trading activity," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    5. Karsten Müller, 2022. "German forecasters’ narratives: How informative are German business cycle forecast reports?," Empirical Economics, Springer, vol. 62(5), pages 2373-2415, May.
    6. Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2024. "Google search trends and stock markets: Sentiment, attention or uncertainty?," International Review of Financial Analysis, Elsevier, vol. 91(C).
    7. Gaoshan Wang & Guangjin Yu & Xiaohong Shen, 2020. "The Effect of Online Investor Sentiment on Stock Movements: An LSTM Approach," Complexity, Hindawi, vol. 2020, pages 1-11, December.
    8. Nattapat Luenglertpatboon & Chayanon Phucharoen & Aziz Nanthaamornphong, 2026. "Google Trends and stock price movements: an empirical analysis of investor attention using the ARDL approach," SN Business & Economics, Springer, vol. 6(4), pages 1-26, April.
    9. Papadamou, Stephanos & Fassas, Athanasios P. & Kenourgios, Dimitris & Dimitriou, Dimitrios, 2023. "Effects of the first wave of COVID-19 pandemic on implied stock market volatility: International evidence using a google trend measure," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).
    10. 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.
    11. Wang, Gaoshan & Yu, Guangjin & Shen, Xiaohong, 2021. "The effect of online environmental news on green industry stocks: The mediating role of investor sentiment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    12. Shah, Syed Faisal & Albaity, Mohamed, 2022. "The role of trust, investor sentiment, and uncertainty on bank stock return performance: Evidence from the MENA region," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    13. Seyed Alireza Athari & Dervis Kirikkaleli & Tomiwa Sunday Adebayo, 2023. "World pandemic uncertainty and German stock market: evidence from Markov regime-switching and Fourier based approaches," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1923-1936, April.
    14. Arnold, Ivo J.M., 2020. "Internet search volumes of UK banks during the crisis: The role of banking structure and business model," Global Finance Journal, Elsevier, vol. 45(C).
    15. Papadamou, Stephanos & Fassas, Athanasios & Kenourgios, Dimitris & Dimitriou, Dimitrios, 2020. "Direct and Indirect Effects of COVID-19 Pandemic on Implied Stock Market Volatility: Evidence from Panel Data Analysis," MPRA Paper 100020, University Library of Munich, Germany.
    16. Rameeza Andleeb & Arshad Hassan, 2025. "Nonlinear Relationship Between Investor Sentiment and Conditional Volatility in Emerging Equity Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 32(1), pages 147-165, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:bpj:germec:v:20:y:2019:i:1:p:1-28. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Peter Golla (email available below). General contact details of provider: https://www.degruyterbrill.com .

    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.