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ROSARIO NUNZIO MANTEGNA

Dominating Clasp of the Financial Sector Revealed by Partial Correlation Analysis of the Stock Market

  • Autori: Kenett, D.; Tumminello, M.; Madi, A.; Gur Gershgoren, G.; Mantegna, R.; Ben Jacob, E.
  • Anno di pubblicazione: 2010
  • Tipologia: Articolo in rivista (Articolo in rivista)
  • Parole Chiave: CORRELATION-BASED NETWORKS; PORTFOLIO OPTIMIZATION; CORRELATION-MATRICES; TIME-SERIES; INFORMATION

Abstract

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.

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