Copula-based measures of dependence structure in assets returns
AbstractCopula modeling has become an increasingly popular tool in finance to model assets returns dependency. In essence, copulas enable us to extract the dependence structure from the joint distribution function of a set of random variables and, at the same time, to separate the dependence structure from the univariate marginal behavior. In this study, based on U.S. stock data, we illustrate how tail-dependency tests may be misleading as a tool to select a copula that closely mimics the dependency structure of the data. This problem becomes more severe when the data is scaled by conditional volatility and/or filtered out for serial correlation. The discussion is complemented, under more general settings, with Monte Carlo simulations.
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Bibliographic InfoPaper provided by Centro de Economía Aplicada, Universidad de Chile in its series Documentos de Trabajo with number 228.
Date of creation: 2006
Date of revision:
Other versions of this item:
- Fernandez, Viviana, 2008. "Copula-based measures of dependence structure in assets returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3615-3628.
- NEP-ALL-2007-04-21 (All new papers)
- NEP-CMP-2007-04-21 (Computational Economics)
- NEP-ECM-2007-04-21 (Econometrics)
- NEP-FMK-2007-04-21 (Financial Markets)
- NEP-RMG-2007-04-21 (Risk Management)
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