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An Asymmetric Block Dynamic Conditional Correlation Multivariate GARCH Model

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  • Vargas, Gregorio A.

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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Bibliographic 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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Keywords: asymmetric effect; block dynamic conditional correlation; multivariate GARCH;

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Cited by:
  1. Linyue Li & Nan Zhang & Thomas D. Willett, 2012. "Measuring macroeconomic and financial market interdependence: a critical survey," Journal of Financial Economic Policy, Emerald Group Publishing, vol. 4(2), pages 128-145, June.
  2. Hakim, Abdul & McAleer, Michael, 2009. "Forecasting conditional correlations in stock, bond and foreign exchange markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2830-2846.

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