ABSTRACT
This chapter deals with the use of automated analysis of news and market sentiment data for trading. This is essential because market consists of noise traders who may trade on sentiment and the short-term price movements are not easily explained by the relevant indicators that may be slow to vary; the commonly studied stock related indicators such as earnings announcements occur only on periodic basis. The sentiment analysis captures an understanding of how noise traders are likely to trade and this topic can be considered as part of the emerging area of Behavioral Finance. This chapter presents an analysis of sentiments captured in stock related tweets and refined by Natural Language Processing techniques with an application to trading strategies.
