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Extraction of Information Content Exchange in Financial Markets by an Entropy Analysis

机译:熵分析提取金融市场中的信息内容交换

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Recently, there has been an explosive interest in the literature about modeling and forecasting volatility in financial markets. Many researches have focused on energy markets and oil volatility index (OVX). In this article, we aim first at showing if there is an exchange of information between two stock time series, and then at evaluating what is the direction of this information flow. In particular, we propose an entropy-based approach that exploits two objective metrics, namely Mutual Information (MI) and Transfer Entropy (TE), that does not require a parametric model and is directly applicable on the data. The experimental outcomes, applied on Brent and WTI crude oil prices and their volatility index for the period from May 10, 2007 till July 03, 2018, demonstrate the effectiveness of the proposed method.
机译:最近,对金融市场中的建模和预测波动性的文献产生了爆发力的兴趣。许多研究都集中在能量市场和油波动指数(OVX)上。在本文中,我们首先展示了两个库存时间序列之间的信息交换,然后在评估该信息流的方向时。特别是,我们提出了一种基于熵的方法,该方法利用了两个目标度量,即互信息(MI)和传输熵(TE),其不需要参数模型,并且是直接适用于数据的。在2007年5月10日至2018年7月10日至7月10日,展示了布伦特和WTI原油价格的实验结果及其波动指数,证明了该方法的有效性。

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