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Academic Journal of Business & Management, 2023, 5(14); doi: 10.25236/AJBM.2023.051401.

Study on the Correlation between Investor Sentiment and Stock Price Co-movement


Siqiang Gong, Hua Fang

Corresponding Author:
Hua Fang

Business School, University of Shanghai for Science and Technology, Shanghai, 200093, China


This paper empirically investigates the correlation between investor sentiment and stock price co-movement through a panel vector autoregressive model. The study divides investor sentiment into market sentiment, which represents the overall market attitude, and retail sentiment, which represents the attitude of retail investors, while the studied stock price co-movement refers to the linkage between individual stocks and the market. It is found that the relationship between investor sentiment and stock price co-movement shows a unidirectional effect. Investor sentiment can have an impact on stock price co-movement, however, stock price co-movement cannot significantly affect investor sentiment. Investor sentiment has a negative impact on stock price co-movement. Market sentiment has a significant impact on stock price co-movement, but retail sentiment has a non-significant impact on stock price linkage. This study is a further expansion of the research field on investor sentiment and stock price co-movement, providing a new regulatory perspective for regulator authorities and a new reference for investors to make rational investments.


Investor Sentiment; Stock Price Co-movement; PVAR Model

Cite This Paper

Siqiang Gong, Hua Fang. Study on the Correlation between Investor Sentiment and Stock Price Co-movement. Academic Journal of Business & Management (2023) Vol. 5, Issue 14: 1-8. https://doi.org/10.25236/AJBM.2023.051401.


[1] Dong ZY, Kang ZP. Behavioral finance and the debate on the efficient market hypothesis[J]. Ningxia Social Science, 2006(4): 43-48.

[2] Yu QL. Research on the impact of investor sentiment on stock price linkage [D]. Southwest Jiaotong University, 2018.

[3] Duan JJ, Liu HZ, Zeng JP. Analysis of information content of Chinese stock online forums[J]. Financial Research, 2017(10): 178-192.

[4] Lei B, Liu Z, Song Y. On stock volatility forecasting based on text mining and deep learning under high‐frequency data [J]. Journal of Forecasting, 2021, 40(8): 1596-1610.

[5] Roll R. R-squared [J]. Journal of finance, 1988, 43(3): 541-566.

[6] Sigmund M, Ferstl R. Panel vector autoregression in R with the package panelvar[J]. The Quarterly Review of Economics and Finance, 2021, 80: 693-720.