Identifying common dynamic features in stock returns

Jorge Caiado () and Nuno Crato ()

MPRA Paper from University Library of Munich, Germany

Abstract: This paper proposes spectral and asymmetric-volatility based methods for cluster analysis of stock returns. Using the information about both the periodogram of the squared returns and the estimated parameters in the TARCH equation, we compute a distance matrix for the stock returns. Clusters are formed by looking to the hierarchical structure tree (or dendrogram) and the computed principal coordinates. We employ these techniques to investigate the similarities and dissimilarities between the "blue-chip" stocks used to compute the Dow Jones Industrial Average (DJIA) index. For reference, we investigate also the similarities among stock returns by mean and squared correlation methods.

Keywords: Asymmetric effects; Cluster analysis; DJIA stock returns; Periodogram; Threshold ARCH model; Volatility (search for similar items in EconPapers)
JEL-codes: C32 G1 G10 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2009-04
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http://mpra.ub.uni-muenchen.de/15240/ orginal version
http://mpra.ub.uni-muenchen.de/15241/ revised version

Related works:
Working Paper: Identifying common dynamic features in stock returns (2009)
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Persistent link: http://EconPapers.repec.org/RePEc:pra:mprapa:15240

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