英文标题：
《Partial correlation analysis: Applications for financial markets》
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作者：
Dror Y. Kenett, Xuqing Huang, Irena Vodenska, Shlomo Havlin, and H.
  Eugene Stanley
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最新提交年份：
2014
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英文摘要：
  The presence of significant cross-correlations between the synchronous time evolution of a pair of equity returns is a well-known empirical fact. The Pearson correlation is commonly used to indicate the level of similarity in the price changes for a given pair of stocks, but it does not measure whether other stocks influence the relationship between them. To explore the influence of a third stock on the relationship between two stocks, we use a partial correlation measurement to determine the underlying relationships between financial assets. Building on previous work, we present a statistically robust approach to extract the underlying relationships between stocks from four different financial markets: the United States, the United Kingdom, Japan, and India. This methodology provides new insights into financial market dynamics and uncovers implicit influences in play between stocks. To demonstrate the capabilities of this methodology, we (i) quantify the influence of different companies and, by studying market similarity across time, present new insights into market structure and market stability, and (ii) we present a practical application, which provides information on the how a company is influenced by different economic sectors, and how the sectors interact with each other. These examples demonstrate the effectiveness of this methodology in uncovering information valuable for a range of individuals, including not only investors and traders but also regulators and policy makers.
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中文摘要：
一对股票收益率的同步时间演化之间存在显著的交叉相关性是众所周知的经验事实。皮尔逊相关性通常用于表示给定一对股票价格变化的相似程度，但它不能衡量其他股票是否影响它们之间的关系。为了探索第三种股票对两种股票之间关系的影响，我们使用偏相关度量来确定金融资产之间的潜在关系。在之前工作的基础上，我们提出了一种统计稳健的方法来提取来自四个不同金融市场的股票之间的潜在关系：美国、英国、日本和印度。这种方法为金融市场动态提供了新的见解，并揭示了股票之间的隐性影响。为了证明这种方法的能力，我们（i）量化了不同公司的影响，并通过研究不同时间的市场相似性，对市场结构和市场稳定性提出了新的见解，以及（ii）我们提出了一个实际应用，提供了关于不同经济部门如何影响公司的信息，以及各部门之间的互动。这些例子证明了这种方法在发现对一系列个人有价值的信息方面的有效性，这些个人不仅包括投资者和交易员，还包括监管机构和政策制定者。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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一级分类：Quantitative Finance        数量金融学
二级分类：Trading and Market Microstructure        交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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