An entropy based analysis of the relationship between the DOW JONES Index and the TRNA Sentiment series [Conference paper]
21st Annual Conference of the Multinational Finance Society
Multinational Finance Society
School of Business / Markets and Services Research Centre
This paper features an analysis of the relationship between the DOW JONES Industrial Average Index (DJIA) and a sentiment news series using daily data obtained from the Thomson Reuters News Analytics (TRNA)1 provided by SIRCA (The Securities Industry Research Centre of the Asia Pacific). The re-cent growth in the availability of on-line financial news sources such as internet news and social media sources provides instantaneous access to financial news. Various commercial agencies have started developing their own filtered financial news feeds which are used by investors and traders to support their algorithmic trading strategies. Thomson Reuters News Analytics (TRNA)2 is one such data set. In this study we use the TRNA data set to construct a series of daily sentiment scores for Dow Jones Industrial Average (DJIA) stock index component companies. We use these daily DJIA market sentiment scores to study the relationship between financial news sentiment scores and the DJIA return series using entropy measures. The entropy and Mutual Information (MI) statistics permit an analysis of the amount of information within the sentiment series and its relationship to the DJIA and an indication of the relationship changes over time.