Clustering stocks using partial correlation coefficients

Sean S. Jung and Woojin Chang

Physica A: Statistical Mechanics and its Applications, 2016, vol. 462, issue C, 410-420

Abstract: A partial correlation analysis is performed on the Korean stock market (KOSPI). The difference between Pearson correlation and the partial correlation is analyzed and it is found that when conditioned on the market return, Pearson correlation coefficients are generally greater than those of the partial correlation, which implies that the market return tends to drive up the correlation between stock returns. A clustering analysis is then performed to study the market structure given by the partial correlation analysis and the members of the clusters are compared with the Global Industry Classification Standard (GICS). The initial hypothesis is that the firms in the same GICS sector are clustered together since they are in a similar business and environment. However, the result is inconsistent with the hypothesis and most clusters are a mix of multiple sectors suggesting that the traditional approach of using sectors to determine the proximity between stocks may not be sufficient enough to diversify a portfolio.

Keywords: Financial market; Stylized facts; Pearson correlation; Partial correlation; Agglomerative clustering (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:462:y:2016:i:c:p:410-420

DOI: 10.1016/j.physa.2016.06.094

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