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An Asymmetric Block Dynamic Conditional Correlation Multivariate GARCH Model

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Author Info
Vargas, Gregorio A.

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Abstract

The Block DCC model for determining dynamic correlations within and between groups of financial asset returns is extended to account for asymmetric effects. Simulation results show that the Asymmetric Block DCC model is competitive in in-sample forecasting and performs better than alternative DCC models in out-of-sample forecasting of conditional correlation in the presence of asymmetric effect between blocks of asset returns. Empirical results demonstrate that the model is able to capture the asymmetries in conditional correlations of some blocks of currencies in East Asia in the turbulent years of the late 1990s.

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File URL: http://mpra.ub.uni-muenchen.de/189/
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Publisher Info
Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 189.

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Date of creation: Jan 2006
Date of revision: Aug 2006
Publication status: Published in The Philippine Statistician 1-2.55(2006): pp. 83-102
Handle: RePEc:pra:mprapa:189

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Related research
Keywords: asymmetric effect block dynamic conditional correlation multivariate GARCH

Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models
G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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