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What is the Best Approach to Measure the Interdependence between Different Markets?

Author

Listed:
  • Avouyi-Dovi, S.
  • Guégan, D.
  • Ladoucette, S.

Abstract

In order to measure the interdependence between different markets, we investigate and compare different measures of dependence including cross-correlation, conditional correlation, concordance and correlation in tails. In the latter case, we use the notion of copula and we define two kinds of diagnoses which enable us to adjust the joint empirical tail distribution in the case of two or three markets for the best copulas. In particular, this approach makes it possible to understand the evolution of the interdependence of more than two markets in the tails, in particular, when extremal values (which correspond to a shock) induce some turmoil in the evolution of the markets.

Suggested Citation

  • Avouyi-Dovi, S. & Guégan, D. & Ladoucette, S., 2002. "What is the Best Approach to Measure the Interdependence between Different Markets?," Working papers 95, Banque de France.
    • Handle: RePEc:bfr:banfra:95
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    References listed on IDEAS

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    3. Brian H. Boyer & Michael S. Gibson & Mico Loretan, 1997. "Pitfalls in tests for changes in correlations," International Finance Discussion Papers 597, Board of Governors of the Federal Reserve System (U.S.).
    4. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
    5. C John McDermott & Alasdair Scott, 1999. "Concordance in business cycles," Reserve Bank of New Zealand Discussion Paper Series G99/7, Reserve Bank of New Zealand.
    6. Don Harding & Adrian Pagan, 1999. "Knowing the Cycle," Melbourne Institute Working Paper Series wp1999n12, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    7. Raymond Brummelhuis & Dominique Guegan, 2005. "Multi-period conditional distribution functions for heteroscedastic models with applications to VaR," Post-Print halshs-00179336, HAL.
    8. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
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    Cited by:

    1. Michel Beine & Gunther Capelle-Blancard & Helene Raymond, 2008. "International nonlinear causality between stock markets," The European Journal of Finance, Taylor & Francis Journals, vol. 14(8), pages 663-686.
    2. Dominique Guegan, 2011. "Contagion Between the Financial Sphere and the Real Economy. Parametric and non Parametric Tools: A Comparison," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00185373, HAL.
    3. Dominique Guegan, 2003. "A prospective study of the k-factor Gegenbauer processes with heteroscedastic errors and an application to inflation rates," Post-Print halshs-00201314, HAL.
    4. Maugis, Pierre-André G., 2019. "Correlation extrapolated," Statistics & Probability Letters, Elsevier, vol. 145(C), pages 89-95.
    5. Dominique Guegan, 2011. "Contagion Between the Financial Sphere and the Real Economy. Parametric and non Parametric Tools: A Comparison," PSE-Ecole d'économie de Paris (Postprint) halshs-00185373, HAL.

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    More about this item

    Keywords

    Interdependence; Conditional correlation; Concordance; Functions copulas.;
    All these keywords.

    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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