私人信息检索
公共信息
差异(会计)
互联网
库存(枪支)
计量经济学
噪音(视频)
业务
股票市场
金融经济学
经济
计算机科学
会计
统计
数学
互联网隐私
万维网
工程类
人工智能
图像(数学)
古生物学
生物
机械工程
马
作者
Jonathan Brogaard,Thanh Huong Nguyen,Tālis J. Putniņš,Eliza Wu
摘要
Abstract We develop a return variance decomposition model to distinguish the roles of different types of information and noise in stock price movements. We disentangle four components: noise, private firm-specific information revealed through trading, firm-specific information revealed through public sources and market-wide information. Overall, we find that 31$\%$ of the return variance is from noise, 24$\%$ from private firm-specific information, 37$\%$ from public firm-specific information and 8$\%$ from market-wide information. Since the mid-1990s, there has been a dramatic decline in noise and an increase in firm-specific information, consistent with increasing market efficiency. The Internet Appendix that accompanies this paper can be obtained here: https://bit.ly/3FcV9UR
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