This paper provides an extension of the Dynamic Conditional Correlation model of Engle (2002) by allowing both the unconditional correlation and the parameters to be driven by an unobservable Markov chain. We provide the estimation algorithm and perform an empirical analysis of the contagion phenomenon in which our model is compared to the traditional CCC and DCC representations.

Multivariate Markov Switching Dynamic Conditional Correlation GARCH representations for contagion analysis

BILLIO, Monica;CAPORIN, Massimiliano
2005-01-01

Abstract

This paper provides an extension of the Dynamic Conditional Correlation model of Engle (2002) by allowing both the unconditional correlation and the parameters to be driven by an unobservable Markov chain. We provide the estimation algorithm and perform an empirical analysis of the contagion phenomenon in which our model is compared to the traditional CCC and DCC representations.
2005
14/2
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/29049
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 65
  • ???jsp.display-item.citation.isi??? ND
social impact