Search attention and opinion divergence in explaining retail investor behavior
https://doi.org/10.55959/MSU0130-0105-6-60-5-1
Abstract
The current study demonstrates an approach of analyzing the returns of Russian issuers’ stocks by taking into account the behavior of individual investors based on the application of metrics of divergence of users’ opinions of online investment platforms and the attention of investors themselves. These opinions, i.e. text messages, were collected using machine learning and deep learning algorithms. The statistics of search queries on economic-political and investment topics is used as a proxy for the attention of private investors to analyze stock returns. The text database consists of more than 4.3 million messages on Tinkoff Pulse, SmartLab and MFD platforms. Stock price behavior is also analyzed by accounting for the attention of retail market participants. The purpose of the paper is to assess the impact of divergence in opinions and attention of private investors to the returns of shares of issuers under consideration on the Russian stock market. The research methodology includes textual and econometric analysis. The author applies augmentation of training text array and training machine learning and underlying deep learning models for automatic classification. Two econometric methods of estimating regressors are used to analyze stock price behavior: generalized method of moments and generalized least squares method. The findings show: (1) divergence of opinions has an impact on stock returns only on the days of discussions; (2) private investors’ attention to economic-political and investment topics has an impact only on the future behavior of stock prices; (3) depending on the level of volatility (risk) of stocks, there are some unstable patterns of the correlation between disagreements among the users of analysed platforms and stock returns.
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For citations:
Fayzulin M.S. Search attention and opinion divergence in explaining retail investor behavior. Lomonosov Economics Journal. 2025;60(5):3-41. (In Russ.) https://doi.org/10.55959/MSU0130-0105-6-60-5-1
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