Partial correlation analysis: applications for financial markets
Files
Accepted manuscript
Date
2015-04-03
Authors
Kenett, Dror Y.
Huang, Xuqing
Vodenska, Irena
Havlin, Shlomo
Stanley, H. Eugene
Version
Accepted manuscript
OA Version
Citation
Dror Y Kenett, Xuqing Huang, Irena Vodenska, Shlomo Havlin, H Eugene Stanley. 2015. "Partial correlation analysis: applications for financial markets." QUANTITATIVE FINANCE, Volume 15, Issue 4, pp. 569 - 578. https://doi.org/10.1080/14697688.2014.946660
Abstract
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.