An analysis of cross-correlations in an emerging market

Diane Wilcox and Tim Gebbie

Physica A: Statistical Mechanics and its Applications, 2007, vol. 375, issue 2, 584-598

Abstract: We apply random matrix theory to compare correlation matrix estimators C obtained from emerging market data. The correlation matrices are constructed from 10 years of daily data for stocks listed on the Johannesburg stock exchange (JSE) from January 1993 to December 2002. We test the spectral properties of C against random matrix predictions and find some agreement between the distributions of eigenvalues, nearest neighbour spacings, distributions of eigenvector components and the inverse participation ratios for eigenvectors. We show that interpolating both missing data and illiquid trading days with a zero-order hold increases agreement with RMT predictions. For the more realistic estimation of correlations in an emerging market, we suggest a pairwise measured-data correlation matrix. For the data set used, this approach suggests greater temporal stability for the leading eigenvectors. An interpretation of eigenvectors in terms of trading strategies is given, as opposed to classification by economic sectors.

Keywords: Random matrices; Cross-correlations; Finance; Emerging markets (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (37)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:375:y:2007:i:2:p:584-598

DOI: 10.1016/j.physa.2006.10.030

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