The Handbook of Sentiment Analysis in Finance provides a comprehensive collection of relevant research results, which cover the financial applications of sentiment classification in general, and sentiment quantification in particular.
This is an emerging and evolving topic area that has been impacted by (i) growth in social media, (ii) online information sources, (iii) evolution of data sciences (iv) continued developments in machine learning and artificial intelligence and (v) maturing of financial technologies (fintech), which exploit speed of communications and computations. Whereas early applications of sentiment analysis have been in the domain of equities, the recent developments have covered other asset classes, specifically, fixed income, foreign exchange, energy products and commodities. In all these domains we have focused on three major application areas which are automated trading, fund rebalancing and risk quantification and control. Building on the success of The Handbook of News Analytics in Finance (published 2011), this updated volume describes the explosive developments that have occurred in the last five years in this domain.
A growing consumer interest in sentiment analysis and its possible applications, and new media sources influencing market sentiment have motivated the editors to create this compilation of research studies.
