Identifying common dynamic features in stock returns

Jorge Caiado and Nuno Crato ()

No 902, CEMAPRE Working Papers from Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon

Abstract: This paper proposes volatility and spectral based methods for cluster analysis of stock returns. Using the information about both the estimated parameters in the threshold GARCH (or TGARCH) equation and the periodogram of the squared returns, 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.

Keywords: Asymmetric effects; Cluster analysis; DJIA stock returns; Periodogram; Threshold GARCH model; Volatility (search for similar items in EconPapers)
Pages: 22 pages
Date: 2009-05
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-fmk
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://cemapre.iseg.utl.pt/archive/preprints/383.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 500 Can't connect to cemapre.iseg.utl.pt:80 (No such host is known. )

Related works:
Working Paper: Identifying common dynamic features in stock returns (2009)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cma:wpaper:0902

Access Statistics for this paper

More papers in CEMAPRE Working Papers from Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon Contact information at EDIRC.
Bibliographic data for series maintained by Helena Lima ( this e-mail address is bad, please contact ).