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

被引:12
|
作者
Allen, David E. [1 ,2 ]
McAleer, Michael [3 ,4 ,5 ,6 ]
Singh, Abhay K. [7 ]
机构
[1] Univ South Australia, Ctr Appl Financial Studies, Adelaide, SA, Australia
[2] Univ Sydney, Sch Math & Stat, Sydney, NSW, Australia
[3] Natl Tsing Hua Univ, Coll Technol Management, Dept Quantitat Finance, Hsinchu, Taiwan
[4] Erasmus Univ, Econometr Inst, Erasmus Sch Econ, Rotterdam, Netherlands
[5] Tinbergen Inst, Amsterdam, Netherlands
[6] Univ Complutense Madrid, Dept Quantitat Econ, Madrid, Spain
[7] Edith Cowan Univ, Sch Business & Law, Perth, WA, Australia
关键词
DJIA; sentiment; entropy; TRNA; information; INVESTOR SENTIMENT; INFORMATION;
D O I
10.1080/00036846.2016.1203067
中图分类号
F [经济];
学科分类号
02 ;
摘要
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.
引用
收藏
页码:677 / 692
页数:16
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