News or Noise? Using Twitter to Identify and Understand Company-specific News Flow

被引：99

作者：

Sprenger, Timm O. ^{[1
]}

Sandner, Philipp G. ^{[1
]}

Tumasjan, Andranik ^{[1
]}

Welpe, Isabell M. ^{[1
]}

机构：

[1] TUM, TUM Sch Management, D-80333 Munich, Germany

来源：

JOURNAL OF BUSINESS FINANCE & ACCOUNTING | 2014年 / 41卷 / 7-8期

关键词：

event study; news events; information leakage; market reaction; computational linguistics; BAD-NEWS; INTERNET; INFORMATION; MARKET; EVENTS; FIRMS; UNDERREACTION; OVERREACTION; PERFORMANCE; RETURNS;

D O I：

10.1111/jbfa.12086

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

This study presents a methodology for identifying a broad range of real-world news events based on microblogging messages. Applying computational linguistics to a unique dataset of more than 400,000 S&P 500 stock-related Twitter messages, we distinguish between good and bad news and demonstrate that the returns prior to good news events are more pronounced than for bad news events. We show that the stock market impact of news events differs substantially across different categories.

引用

页码：791 / 830

页数：40

共 63 条

[1] THE POST-MERGER PERFORMANCE OF ACQUIRING FIRMS - A REEXAMINATION OF AN ANOMALY [J].