 Multivariate FIAPARCH modelling of financial markets with dynamic correlations in times of crisisMenelaos Karanasos, Stavroula Yfanti and Michail Karoglou International Review of Financial Analysis, 2016, vol. 45, issue C, 332-349 Abstract: This paper applies the vector AR-DCC-FIAPARCH model to eight national stock market indices' daily returns from 1988 to 2010, taking into account the structural breaks of each time series linked to the Asian and the recent Global financial crisis. We find significant cross effects, as well as long range volatility dependence, asymmetric volatility response to positive and negative shocks, and the power of returns that best fits the volatility pattern. One of the main findings of the model analysis is the higher dynamic correlations of the stock markets after a crisis event, which means increased contagion effects between the markets. The fact that during the crisis the conditional correlations remain on a high level indicates a continuous herding behaviour during these periods of increased market volatility. Finally, during the recent Global financial crisis the correlations remain on a much higher level than during the Asian financial crisis. Keywords: Contagion effects; Dynamic conditional correlation; Financial crisis; Long memory; Multivariate; GARCH; Structural breaks (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:45:y:2016:i:c:p:332-349 DOI: 10.1016/j.irfa.2014.09.002 Access Statistics for this article International Review of Financial Analysis is currently edited by B.M. Lucey More articles in International Review of Financial Analysis from Elsevier |
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