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Exploring local dependence

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Author Info
Klaus Abberger () (IFO Munich)

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Abstract

This paper discusses two graphical methods for the investigation of local association of two continuous random variables. Often, scalar dependence measures, such as correlation, cannot reflect the complex dependence structure of two variables. However, dependence graphs have the potential to assess a far richer class of bivariate dependence structures. The two graphical methods discussed in this article are the chi-plot and the local dependence map. After the introduction of these methods they are applied to different data sets. These data sets contain simulated data and daily stock return series. With these examples the application possibilities of the two local dependence graphs are shown.

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Publisher Info
Paper provided by Center of Finance and Econometrics, University of Konstanz in its series CoFE Discussion Paper with number 02-14.

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Length: 14 pages
Date of creation: Apr 2002
Date of revision:
Handle: RePEc:knz:cofedp:0214

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Related research
Keywords: Association; bivariate distribution; chi-plot; copula; correlation; kernel smoothing; local dependence; permutation test;

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  1. Fisher N. I. & Switzer P., 2001. "Graphical Assessment of Dependence: Is a Picture Worth 100 Tests?," The American Statistician, American Statistical Association, vol. 55, pages 233-239, August. [Downloadable!] (restricted)
  2. Jones, M. C., 1998. "Constant Local Dependence," Journal of Multivariate Analysis, Elsevier, vol. 64(2), pages 148-155, February. [Downloadable!] (restricted)
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This page was last updated on 2009-11-26.

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