An Analysis of the Temporal Impact of Investor Sentiment and Attention on Stock Liquidity Using Deep Learning

被引：0
|
作者：
Wang, Gaoshan [1 ,2 ]
Wang, Zhiyi [1 ]
Chen, Mingyue [1 ]
Shen, Xiaohong [3 ]
机构：
[1] Shandong Univ Finance & Econ, Sch Management Sci & Engn, 7366 Erhuan Dong Rd, Jinan 250014, Peoples R China
[2] Shandong Univ Finance & Econ, Inst Digital Econ, 7366 Erhuan Dong Rd, Jinan 250014, Peoples R China
[3] Shandong Univ Finance & Econ, Sch Comp Sci & Technol, 7366 Erhuan Dong Rd, Jinan 250014, Peoples R China
来源：
COMPUTATIONAL ECONOMICS | 2025年
关键词：
Investor sentiment; Investor attention; Stock liquidity; Trading hours; Non-trading hours; Deep Learning;
D O I：
10.1007/s10614-025-10918-z
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
The impact of investor sentiment and attention on stock liquidity is a hot topic. However, prior research has not distinguished the effects of different time periods' sentiment and attention. The study derived investor sentiment and attention from online comments and calculated sentiment and attention indices on trading and non-trading hours, the effects of which on stock liquidity were subsequently analyzed by regression models. Previous research shows that investor sentiment positively impacts stock liquidity, aligning with our findings using sentiment data from 24 h before market opening. However, when divided into trading and non-trading periods, sentiment during trading hours has no significant impact on liquidity, while non-trading hours show a significant positive impact. In contrast, investor attention consistently positively impacts liquidity, regardless of trading periods.
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页数：29
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