期刊
JOURNAL OF ECONOMIC SURVEYS
卷 30, 期 2, 页码 356-369出版社
WILEY
DOI: 10.1111/joes.12102
关键词
Big data; Financial predictions; Machine learning; Sentiment analysis; Text mining; Trading strategies; Web mining
类别
A blindfolded chimpanzee throwing darts at The Wall Street Journal could select a portfolio that would do as well as the (stock market) experts' [Malkiel (2003) The efficient market hypothesis and its critics. Journal of Economic Perspectives 17(1): 59-82)]. However, what if this chimpanzee could browse the Internet before throwing any darts? In this paper, we ask whether online news has any influence on the financial market, and we also investigate how much influence it has. We explore the burgeoning literature on the predictability of financial movements using online information and report its mixed findings. In addition, we collate the efforts of various disciplines, including economics, text mining, sentiment analysis and machine learning, and we offer suggestions for future research.
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