OVERNIGHT SENTIMENT DIVERGENCE AND OPENING PRICE FORMATION: EVIDENCE FROM RETAIL INVESTOR TEXT
DOI:
https://doi.org/10.55197/qjssh.v7i4.1268Keywords:
investor sentiment, sentiment divergence, opening returns, retail investors, textual analysisAbstract
This research study examines how the investor disagreement formed during non-trading hours influences stock price formation at the market open. Using a large dataset of retail investor forum posts from China’s A-share market; this research study constructs an entropy-based measure of overnight sentiment divergence derived from text-level sentiment classification. The empirical results reveal a consistent pattern: higher sentiment divergence is associated with lower opening returns. This relationship remains robust after controlling for firm characteristics, market-wide overnight movements, and corporate announcements. Importantly, the sentiment divergence retains explanatory power even after accounting for average sentiment, indicating that disagreement captures an independent dimension of investor behavior beyond sentiment direction. Further analysis shows that the effect is significantly stronger in stocks with higher trading activity, suggesting that active trading environments amplify the pricing impact of disagreement. Overall, the findings highlight the role of investor belief dispersion as a key factor in short-term price dynamics.
References
[1] Aboody, D., Even-Tov, O., Lehavy, R., Trueman, B. (2018): Overnight returns and firm-specific investor sentiment. – Journal of Financial and Quantitative Analysis 53(2): 485-505.
[2] Agarwal, S., Kumar, S., Goel, U. (2019): Stock market response to information diffusion through internet sources: A literature review. – International Journal of Information Management 45: 118-131.
[3] Akbas, F., Boehmer, E., Jiang, C., Koch, P.D. (2022): Overnight returns, daytime reversals, and future stock returns. – Journal of Financial Economics 145(3): 850-875.
[4] Al-Nasseri, A., Menla Ali, F. (2018): What does investors’ online divergence of opinion tell us about stock returns and trading volume? – Journal of Business Research 86: 166-178.
[5] Araci, D. (2019): FinBERT: Financial sentiment analysis with pre-trained language models. – arXiv Preprint arXiv:1908.10063 11p.
[6] Banerjee, S. (2011): Learning from prices and the dispersion in beliefs. – Review of Financial Studies 24(9): 3025-3068.
[7] Booker, A., Curtis, A., Richardson, V.J. (2023): Investor disagreement, disclosure processing costs, and trading volume: Evidence from social media. – The Accounting Review 98(1): 109-137.
[8] Cao, Z., Kilic, O., Wang, X. (2021): Investor attention, divergence of opinions, and stock returns. – Journal of Behavioral Finance 22(3): 265-279.
[9] Chen, J., Hong, H., Stein, J.C. (2002): Breadth of ownership and stock returns. – Journal of Financial Economics 66(2-3): 171-205.
[10] Chu, G., Goodell, J.W., Li, X. (2024): Are pre-opening periods important? Evidence from Chinese market lunch breaks. – Pacific-Basin Finance Journal 88: 21p.
[11] Chu, X., Wan, X., Qiu, J. (2023): The relative importance of overnight sentiment versus trading-hour sentiment in volatility forecasting. – Journal of Behavioral and Experimental Finance 39: 13p.
[12] Diether, K.B., Malloy, C.J., Scherbina, A. (2002): Differences of opinion and the cross section of stock returns. – Journal of Finance 57(5): 2113-2141.
[13] Doukas, J. A., Kim, C. F., Pantzalis, C. (2006): Divergence of opinion and equity returns. – Journal of Financial and Quantitative Analysis 41(3): 573-606.
[14] Fedyk, A. (2021): Disagreement after news: Gradual information diffusion or differences of opinion? – Review of Asset Pricing Studies 11(3): 465-501.
[15] Garfinkel, J.A., Sokobin, J. (2006): Volume, opinion divergence, and returns: A study of post-earnings announcement drift. – Journal of Accounting Research 44(1): 85-112.
[16] Greene, J.T., Watts, S.G. (1996): Price discovery on the NYSE and the NASDAQ: The case of overnight and daytime news releases. – Financial Management 25(2): 19-42.
[17] Guo, J., Han, X., Li, K., Li, Y. (2025): The nexus of overnight trend and asset prices in China. – Journal of Economic Dynamics and Control 170: 23p.
[18] Ham, H., Ryu, D., Webb, R.I. (2022): The effects of overnight events on daytime trading sessions. – International Review of Financial Analysis 83: 14p.
[19] Ham, H., Ryu, D., Webb, R.I., Yu, J. (2023): How do investors react to overnight returns? Evidence from Korea. – Finance Research Letters 54: 8p.
[20] Huang, A.H., Wang, H., Yang, Y. (2023): FinBERT: A large language model for extracting information from financial text. – Contemporary Accounting Research 40(2): 806-841.
[21] Liu, C., Han, L., Chu, G. (2023): The effect of overnight corporate announcements on price discovery. – Finance Research Letters 53: 5p.
[22] Liu, X., Hou, C., Zhu, S., Chen, H. (2024): The asymmetric effect of information shock on overnight and intraday expected returns: Evidence from the Chinese A-share stock market. – Pacific-Basin Finance Journal 83: 19p.
[23] Meng, Y., Li, X., Xiong, X. (2024): Information shocks and short-term market overreaction: The role of investor attention. – International Review of Financial Analysis 93: 17p.
[24] Merton, R.C. (1987): A simple model of capital market equilibrium with incomplete information. – Journal of Finance 42(3): 483-510.
[25] Miller, E.M. (1977): Risk, uncertainty, and divergence of opinion. – Journal of Finance 32(4): 1151-1168.
[26] Moshirian, F., Nguyen, H.G.L., Pham, P.K. (2012): Overnight public information, order placement, and price discovery during the pre-opening period. – Journal of Banking & Finance 36(10): 2837-2851.
[27] Shannon, C.E. (1948): A mathematical theory of communication. – Bell System Technical Journal 27(3): 379-423.
[28] Siganos, A., Vagenas-Nanos, E., Verwijmeren, P. (2017): Divergence of sentiment and stock market trading. – Journal of Banking & Finance 78: 130-141.
[29] Varian, H.R. (1985): Divergence of opinion in complete markets: A note. – Journal of Finance 40(1): 309-317.
[30] Wang, G.J., Chen, M., Wang, X., Dong, Y., Wang, Z. (2025): Opinion divergence, investor sentiment, and stock liquidity: Evidence from social media. – Investment Analysts Journal 54(2): 167-186.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 JIANBANG NIU, IRWAN IBRAHIM, YAO YANG, MUHAMAD SUKOR JAAFAR, NURA LINA MD ELIAS, JAAFAR PYEMAN
This work is licensed under a Creative Commons Attribution 4.0 International License.
