Time varying vine copulas for multivariate returns (in Russian)

Oleg Groshev
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Oleg Groshev: Barclays Capital, Moscow, Russia

Quantile, 2014, issue 12, 53-67

Abstract: We analyze the multivariate distribution of financial returns using time varying conditional vine copulas. We present the d-Stage Maximum Likelihood (dSML) estimator which is shown to be not only consistent and asymptotically normal, but also more computationally attractive than the standard ML or Patton's 2SML. Using dSML, we fit vine copulas to returns of a portfolio on emerging market currencies.

Keywords: multidimensional time series; vine copulas; dSML estimator; computational efficiency (search for similar items in EconPapers)
JEL-codes: C13 C58 G15 (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:qnt:quantl:y:2014:i:12:p:53-67

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