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

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  • Thomas Dimpfl
  • Vladislav Kleiman

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.

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  • 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.
    • Handle: RePEc:bla:germec:v:20:y:2019:i:1:p:1-28
    DOI: 10.1111/geer.12137
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    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. Karsten Müller, 2022. "German forecasters’ narratives: How informative are German business cycle forecast reports?," Empirical Economics, Springer, vol. 62(5), pages 2373-2415, May.
    5. 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.
    6. 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.
    7. Desagre, Christophe & D’Hondt, Catherine, 2021. "Googlization and retail trading activity," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    8. 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).
    9. 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.
    10. 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.
    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).

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