An entropy-based analysis of the relationship between the DOW JONES Index and the TRNA Sentiment series

ABSTRACT

This article features an analysis of the relationship between the DOW JONES Industrial Average (DJIA) Index and a sentiment news series using daily data obtained from the Thomson Reuters News Analytics (TRNA) provided by SIRCA (The Securities Industry Research Centre of the Asia Pacific). The recent 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. TRNA is one such data set. In this study, we use the TRNA data set to construct a series of daily sentiment scores for DJIA stock index component companies. We use these daily DJIA market sentiment scores to study the relationship between financial news sentiment scores and the stock prices of these companies using entropy measures. The entropy and mutual information (MI) statistics permit an analysis of the amount of information within the sentiment series, its relationship to the DJIA and an indication of how the relationship changes over time.

KEYWORDS:

• DJIA
• sentiment
• entropy
• TRNA
• information

JEL CLASSIFICATION:

• C29
• G12
• G14

Acknowledgements

The authors gratefully acknowledge the support of the QUANTVALLEY/FdR: ‘Quantitative Management Initiative’. We are also grateful to SIRCA for providing the TRNA data sets. We thank an anonymous reviewer for helpful comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ We are grateful to an anonymous reviewer for emphasizing this point.

Additional information

Funding

This work was supported by the QUANTVALLEY/FdR: ‘Quantitative Management Initiative’.