The relative importance of overnight sentiment versus trading-hour sentiment in volatility forecasting

被引:1
|
作者
Chu, Xiaojun [1 ,3 ]
Wan, Xinmin [1 ]
Qiu, Jianying [2 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Sch Management Sci & Engn, Nanjing 210044, Peoples R China
[2] Radboud Univ Nijmegen, Inst Management Res, Dept Econ, Nijmegen, Netherlands
[3] Nanjing Univ Informat Sci & Technol, Sch Management Sci & Engn, 219 Ningliu Rd, Nanjing 210044, Peoples R China
关键词
Volatility forecasting; Trading-hour sentiment; Overnight sentiment; Overnight information; Overnight returns; STOCK-MARKET VOLATILITY; INVESTOR SENTIMENT; INFORMATION-CONTENT; LONG-MEMORY; RETURNS; MODEL; PREMIUM; IMPACT; MEDIA; NOISE;
D O I
10.1016/j.jbef.2023.100826
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
We examine the relative importance of overnight sentiment versus trading-hour sentiment in forecast-ing volatility. Previous studies on investor sentiment either ignore overnight sentiment or aggregate overnight sentiment with trading-hour sentiment. With the help of Chinese sentiment dictionary, we extract investor sentiment from Chinese internet social forums. Our empirical analyses suggest conclusively that investor sentiment significantly affects volatility. In particular, overnight sentiment is more informative than trading-hour sentiment in forecasting volatility, and has higher predictive power than overnight returns, which are widely used to capture overnight information. Our results hold in a series of robustness tests, including in highly volatile subsample, alternative rolling window size, and alternative sentiment proxy.& COPY; 2023 Elsevier B.V. All rights reserved.
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页数:13
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