Dominating clasp of the financial sector revealed by partial correlation analysis of the stock market

What are the dominant stocks which drive the correlations present among stocks traded in a stock market? Can a correlation analysis provide an answer to this question? In the past, correlation based networks have been proposed as a tool to uncover the underlying backbone of the market. Correlation b...

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Bibliographic Details
Published in:PloS one 2010-12, Vol.5 (12), p.e15032-e15032
Main Authors: Kenett, Dror Y, Tumminello, Michele, Madi, Asaf, Gur-Gershgoren, Gitit, Mantegna, Rosario N, Ben-Jacob, Eshel
Format: Article
Language:English
Subjects:
Algorithms
Biology
Construction standards
Correlation
Correlation analysis
Empirical analysis
Financial markets
Forecasting
Humans
Investments - economics
Marketing - economics
Markets
Mathematics
Methods
Models, Economic
Models, Statistical
Models, Theoretical
Networks
New York
Physics
Return on investment
Social and Behavioral Sciences
Stock exchanges
Stocks
Studies
Time series
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Summary:What are the dominant stocks which drive the correlations present among stocks traded in a stock market? Can a correlation analysis provide an answer to this question? In the past, correlation based networks have been proposed as a tool to uncover the underlying backbone of the market. Correlation based networks represent the stocks and their relationships, which are then investigated using different network theory methodologies. Here we introduce a new concept to tackle the above question--the partial correlation network. Partial correlation is a measure of how the correlation between two variables, e.g., stock returns, is affected by a third variable. By using it we define a proxy of stock influence, which is then used to construct partial correlation networks. The empirical part of this study is performed on a specific financial system, namely the set of 300 highly capitalized stocks traded at the New York Stock Exchange, in the time period 2001-2003. By constructing the partial correlation network, unlike the case of standard correlation based networks, we find that stocks belonging to the financial sector and, in particular, to the investment services sub-sector, are the most influential stocks affecting the correlation profile of the system. Using a moving window analysis, we find that the strong influence of the financial stocks is conserved across time for the investigated trading period. Our findings shed a new light on the underlying mechanisms and driving forces controlling the correlation profile observed in a financial market.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0015032