Measuring comovements by regression quantiles

Lorenzo Cappiello, Simone Manganelli and Bruno Gérard

No 501, Working Paper Series from European Central Bank

Abstract: This paper develops a rigorous econometric framework to investigate the structure of codependence between random variables and to test whether it changes over time. Our approach is based on the computation - over both a test and a benchmark period - of the conditional probability that a random variable yt is lower than a given quantile, when the other random variable xt is also lower than its corresponding quantile, for any set of prespecified quantiles. Time-varying conditional quantiles are modeled via regression quantiles. The conditional probability is estimated through a simple OLS regression. We illustrate the methodology by investigating the impact of the crises of the 1990s on the major Latin American equity markets returns. Our results document significant increases in equity return co-movements during crises consistent with the presence of financial contagion. JEL Classification: C14, C22, G15

Keywords: codependence; conditional quantiles; semi-parametric (search for similar items in EconPapers)
Date: 2005-07
Note: 234084
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (33)

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Related works:
Journal Article: Measuring Comovements by Regression Quantiles (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:ecb:ecbwps:2005501

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