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Título:
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An entropy based analysis of the relationship between the DOW JONES Index and the TRNA Sentiment series
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Autores:
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Allen, David E. ;
McAleer, Michael ;
Singh, Abhay K.
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Tipo de documento:
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texto impreso
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Editorial:
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Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE), 2017
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Dimensiones:
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application/pdf
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Nota general:
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cc_by_nc_sa
info:eu-repo/semantics/openAccess
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Idiomas:
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Palabras clave:
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Estado = No publicado
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Materia = Ciencias Sociales: Economía: Econometría
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Materia = Ciencias Sociales: Economía: Mercados bursátiles y financieros
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Tipo = Documento de trabajo o Informe técnico
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Resumen:
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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 Pacic). 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. 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 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.
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En línea:
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https://eprints.ucm.es/id/eprint/40902/1/1701.pdf
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