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Identifying common dynamic features in stock returns

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Author Info
Jorge Caiado () (CEMAPRE, School of Economics and Management (ISEG), Technical University of Lisbon)
Nuno Crato () (CEMAPRE, School of Economics and Management (ISEG), Technical University of Lisbon)

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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.

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Publisher Info
Paper provided by Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon in its series CEMAPRE Working Papers with number 0902.

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Length: 22 pages
Date of creation: May 2009
Date of revision:
Handle: RePEc:cma:wpaper:0902

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Related research
Keywords: Asymmetric effects; Cluster analysis; DJIA stock returns; Periodogram; Threshold GARCH model; Volatility;

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This paper has been announced in the following NEP Reports: References listed on IDEAS
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  1. Schwert, G William, 1989. " Why Does Stock Market Volatility Change over Time?," Journal of Finance, American Finance Association, vol. 44(5), pages 1115-53, December. [Downloadable!] (restricted)
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  2. Engle, Robert F & Ng, Victor K, 1993. " Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-78, December. [Downloadable!] (restricted)
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  3. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 11(4), pages 817-44.
  4. Lorenzo Cappiello & Robert F. Engle & Kevin Sheppard, 2006. "Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 537-572. [Downloadable!] (restricted)
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  5. Caiado, Jorge & Crato, Nuno & Peña, Daniel, 2009. "Comparison of time series with unequal length in the frequency domain," MPRA Paper 15310, University Library of Munich, Germany. [Downloadable!]
  6. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September. [Downloadable!] (restricted)
  7. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(01), pages 122-150, February. [Downloadable!]
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  8. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March. [Downloadable!] (restricted)
  9. Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report 157, Federal Reserve Bank of Minneapolis. [Downloadable!]
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  10. Caiado, Jorge & Crato, Nuno & Pena, Daniel, 2006. "A periodogram-based metric for time series classification," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2668-2684, June. [Downloadable!] (restricted)
  11. Bekaert, Geert & Wu, Guojun, 2000. "Asymmetric Volatility and Risk in Equity Markets," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 13(1), pages 1-42.
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  12. G. Bonanno & G. Caldarelli & F. Lillo & S. Micciche` & N. Vandewalle & R. N. Mantegna, 2004. "Networks of equities in financial markets," Quantitative Finance Papers cond-mat/0401300, arXiv.org. [Downloadable!]
  13. Yu, Chih-Hsien & Wu, Chunchi, 2001. "Economic sources of asymmetric cross-correlation among stock returns," International Review of Economics & Finance, Elsevier, vol. 10(1), pages 19-40. [Downloadable!] (restricted)
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