Systematic analysis of group identification in stock markets

We propose improved methods to identify stock groups using the correlation matrix of stock price changes. By filtering out the marketwide effect and the random noise, we construct the correlation matrix of stock groups in which nontrivial high correlations between stocks are found. Using the filtered correlation matrix, we successfully identify the multiple stock groups without any extra knowledge of the stocks by the optimization of the matrix representation and the percolation approach to the correlation-based network of stocks. These methods drastically reduce the ambiguities while finding stock groups using the eigenvectors of the correlation matrix.
Publisher
AMER PHYSICAL SOC
Issue Date
2005-10
Language
ENG
Keywords

FINANCIAL CORRELATION-MATRICES; CROSS CORRELATIONS; NOISE

Citation

PHYSICAL REVIEW E, v.72, pp.371 - 374

ISSN
1539-3755
DOI
10.1103/PhysRevE.72.046133
URI
http://hdl.handle.net/10203/2262
Appears in Collection
PH-Journal Papers(저널논문)
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