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Quantifiers derived from information theory were used in several papers by econophysicist [http://www.aureliofernandez.net/ Aurelio F. Bariviera] and coauthors in order to assess the degree in the informational efficiency of stock markets.
Quantifiers derived from information theory were used in several papers by econophysicist [http://www.aureliofernandez.net/ Aurelio F. Bariviera] and coauthors in order to assess the degree in the informational efficiency of stock markets.
经济物理学家'''<font color="#ff8000">奥雷里奥·F·巴里维拉 Aurelio F. Bariviera</font>'''和合著者在几篇论文中使用了来自'''<font color="#ff8000">信息论 information theory</font>'''的量词，以评估股票市场信息效率的程度。
Zunino et al. use an innovative statistical tool in the financial literature: the complexity-entropy causality plane. This Cartesian representation establish an efficiency ranking of different markets and distinguish different bond market dynamics. Moreover, the authors conclude that the classification derived from the complexity-entropy causality plane is consistent with the qualifications assigned by major rating companies to the sovereign instruments. A similar study developed by Bariviera et al. explore the relationship between credit ratings and informational efficiency of a sample of corporate bonds of US oil and energy companies using also the complexity–entropy causality plane. They find that this classification agrees with the credit ratings assigned by Moody's.
Zunino et al. use an innovative statistical tool in the financial literature: the complexity-entropy causality plane. This Cartesian representation establish an efficiency ranking of different markets and distinguish different bond market dynamics. Moreover, the authors conclude that the classification derived from the complexity-entropy causality plane is consistent with the qualifications assigned by major rating companies to the sovereign instruments. A similar study developed by Bariviera et al. explore the relationship between credit ratings and informational efficiency of a sample of corporate bonds of US oil and energy companies using also the complexity–entropy causality plane. They find that this classification agrees with the credit ratings assigned by Moody's.
祖尼诺等人，在金融文献中使用创新的统计工具: 复杂性-熵因果关系平面。这种笛卡尔式表示建立了不同市场的效率排名，并区分了不同的债券市场动态。此外，从复杂熵因果关系平面导出的分类结果与主权证券评级公司对主权证券的评级结果一致。同时由 Bariviera 等人开发的一个类似的研究，以美国石油和能源公司债券为样本，运用复杂熵因果关系平面，探讨了信用评级与信息效率的关系。他们发现，这一分类与穆迪给予的信用评级相一致。