Прогнозирование доходности российских акций на основе анализа сентимента инвесторов в социальных сетях

Экономика и математические методы. 2025. Т. 61. № 1. С. 95–108.

Khaziev G., Sokolova T.

The study explores the sentiment of Russian private investors in social networks and its impact on the dynamics of the stock return of 78 companies on the Russian stock market (MOEX) in the period from 2018 to 2022. To take into account sentiment when forecasting returns, the authors RSMI index (Russian social media index) is used, which is based on a unique sample of messages from the most popular social networks among Russian investors - “Telegram” and “Tinkoff Pulse”. The RSMI index includes quantitative (the number of publications in relation to each company) and qualitative (investor reactions) characteristics, allowing to determine the real impact of a particular publication on investors. Using the RSMI index, several models for predicting stock prices of Russian companies were used: lasso regression, random forest, gradient boosting, extreme gradient boosting, ensemble learning and long short-term memory. It is demonstrated that for a wide sample of stocks, indicators of technical and fundamental analysis play a large role in building forecasts of changes in stock returns based on hourly data..

Keywords: фондовый рынок, машинное обучение, акции, сентимент инвесторов