Journal
DECISION SUPPORT SYSTEMS
Volume 61, Issue -, Pages 93-105Publisher
ELSEVIER
DOI: 10.1016/j.dss.2014.01.013
Keywords
Stock market; Sentiment analysis; Web information; Trading strategy
Categories
Funding
- National Natural Science Foundation of China (NSFC) [60803106, 61170133, 91218301]
- Fundamental Research Funds for the Central Universities [JBK120505]
- Sichuan Province Science Foundation
- NSERC [327667-2010]
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Recent studies in behavioral finance discover that emotional impulses of stock investors affect stock prices. The challenge lies in how to quantify such sentiment to predict stock market movements. In this article, we propose a media-aware quantitative trading strategy utilizing sentiment information of Web media. This is achieved by capturing public mood from interactive behaviors of investors in social media and studying the impact of firm-specific news sentiment on stocks along with such public mood. Our experiments on the CSI 100 stocks during a three-month period show that a predictive performance in closeness to the actual future stock price is 0.612 in terms of root mean squared error, the same direction of price movement as the future price is 55.08%, and a simulation trading return is up to 166.11%. (C) 2014 Elsevier B.V. All rights reserved.
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