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

机译:基于熵的道琼斯指数与TRNA情感序列之间关系的分析

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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. © 2016 Informa UK Limited, trading as Taylor \u26 Francis Group
机译:本文使用SIRCA(亚太证券业研究中心)提供的汤森路透新闻分析(TRNA)每日数据,分析道琼斯工业平均指数(DJIA)与情绪新闻系列之间的关系。 。在线金融新闻源(例如,互联网新闻和社交媒体源)的可用性的最近增长提供了对金融新闻的即时访问。各种商业机构已经开始开发自己的过滤后的金融新闻提要,供投资者和交易员用来支持其算法交易策略。 TRNA就是这样一种数据集。在这项研究中,我们使用TRNA数据集来构建DJIA股票指数成分公司的一系列日常情绪得分。我们使用DJIA的每日市场情绪评分,使用熵测度研究金融新闻情绪评分与这些公司的股价之间的关系。熵和互信息(MI)统计信息可以分析情感系列中的信息量,其与DJIA的关系以及关系如何随时间变化的指示。 ©2016 Informa UK Limited,以Taylor \ u26 Francis Group的身分经营

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