Trading Strategies to Exploit Blog and News Sentiment 论文
2010Proceedings of the International AAAI Conference on Web and Social Media引用 249
Stock Market Forecasting MethodsFinancial Markets and Investment StrategiesSentiment Analysis and Opinion Mining
详细信息
- 发表期刊/会议
- Proceedings of the International AAAI Conference on Web and Social Media
- 发表日期
- 2010-05-16
- 发表年份
- 2010
关键词
Stock Market Forecasting MethodsFinancial Markets and Investment StrategiesSentiment Analysis and Opinion Mining
摘要
We use quantitative media (blogs, and news as a comparison) data generated by a large-scale natural language processing (NLP) text analysis system to perform a comprehensive and comparative study on how company related news variables anticipates or reflects the company's stock trading volumes and financial returns. Building on our findings, we give a sentiment-based market-neutral trading strategy which gives consistently favorable returns with low volatility over a long period. Our results are significant in confirming the performance of general blog and news sentiment analysis methods over broad domains and sources. Moreover, several remarkable differences between news and blogs are also identified.