关键词: 投资者情绪, 科创板, 文本挖掘, 联立方程模型, COVID-19

Abstract: Based on the Sci-Tech innovation board listed stocks, this paper focuses on the effect of investor sentiment on the market return before and during the COVID-19. First, we classify the sentiment tendency using daily stock comments in the Eastmoney bar from December of 2019 to March of 2020 using Bi-LSTM deep learning technology and then establish the investor sentiment index. By constructing the two-way fixed effects simultaneous equations model, this paper adopts the 2SLS estimator to investigate the impact of investor sentiment on the return of the Sci-Tech innovation board. Then we verify the difference of this impact between normal market state period and the COVID-19 period. The empirical results and robustness check both reveal that investor sentiment has a significant positive effect on the return, and this positive effect is significantly transmitted through the trading volume at the 1% significance level. The influence of investor sentiment on the market return remains robust in both the normal period and the COVID-19 period. Furthermore, investor sentiment plays a more important role during the outbreak of COVID-19. The results are of important significance not only for the securities market regulators in China to improve the trading mechanism of Sci-Tech innovation board, but also for the small and medium-sized investors to optimize their investment strategy.

Key words: investor sentiment, Sci-Tech innovation board, text mining, simultaneous equations model, COVID-19