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Nonparametric estimation of general multivariate tail dependence and applications to financial time series

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  • Yuri Salazar
  • Wing Ng

Abstract

In order to analyse the entire tail dependence structure among random variables in a multidimensional setting, we present and study several nonparametric estimators of general tail dependence functions. These estimators measure tail dependence in different orthants, complementing the commonly studied positive (lower and upper) tail dependence. This approach is in line with the parametric analysis of general tail dependence. Under this unifying approach the different dependencies are analysed using the associated copulas. We generalise estimators of the lower and upper tail dependence coefficient to the general multivariate tail dependence function and study their statistical properties. Tail dependence measures come as a response to the incapability of the correlation coefficient as an extreme dependence measure. We run a Monte Carlo simulation study to assess the performance of the nonparametric estimators. We also employ selected estimators in two empirical applications to detect and measure the general multivariate non-positive tail dependence in financial data, which popular parametric copula models commonly applied in the financial literature fail to capture. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Yuri Salazar & Wing Ng, 2015. "Nonparametric estimation of general multivariate tail dependence and applications to financial time series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(1), pages 121-158, March.
    • Handle: RePEc:spr:stmapp:v:24:y:2015:i:1:p:121-158
    DOI: 10.1007/s10260-014-0274-7
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    2. Li, Xiaoting & Joe, Harry, 2024. "Multivariate directional tail-weighted dependence measures," Journal of Multivariate Analysis, Elsevier, vol. 203(C).

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    More about this item

    Keywords

    Tail dependence; Copula; Nonparametric estimation; Financial asset returns; C14; C15; C58; G11;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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