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Measuring Comovements by Regression Quantiles

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  • Lorenzo Cappiello
  • Bruno Gérard
  • Arjan Kadareja
  • Simone Manganelli

Abstract

This article develops an econometric framework to investigate the structure of dependence 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 is lower than a given quantile, when another random variable 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 and 2000s on the major Latin American equity markets returns. Our results document significant increases in equity return comovements during crisis times.

Suggested Citation

  • Lorenzo Cappiello & Bruno Gérard & Arjan Kadareja & Simone Manganelli, 2014. "Measuring Comovements by Regression Quantiles," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 12(4), pages 645-678.
  • Handle: RePEc:oup:jfinec:v:12:y:2014:i:4:p:645-678.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbu009
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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