Modelling stock volatilities during financial crises: A time varying coefficient approach

We examine how the most prevalent stochastic properties of key financial time series have been affected during the recent financial crises. In particular we focus on changes associated with the remarkable economic events of the last two decades in the volatility dynamics, including the underlying vo...

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Bibliographic Details
Published in:Journal of empirical finance 2014-12, Vol.29, p.113-128
Main Authors: Karanasos, Menelaos, Paraskevopoulos, Alexandros G., Menla Ali, Faek, Karoglou, Michail, Yfanti, Stavroula
Format: Article
Language:English
Subjects:
Covariance
Economic analysis
Financial crisis
GARCH models
Modelling
Structural breaks
Time varying GARCH models
Volatility
Volatility spillovers
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Summary:We examine how the most prevalent stochastic properties of key financial time series have been affected during the recent financial crises. In particular we focus on changes associated with the remarkable economic events of the last two decades in the volatility dynamics, including the underlying volatility persistence and volatility spillover structure. Using daily data from several key stock market indices, the results of our bivariate GARCH models show the existence of time varying correlations as well as time varying shock and volatility spillovers between the returns of FTSE and DAX, and those of NIKKEI and Hang Seng, which became more prominent during the recent financial crisis. Our theoretical considerations on the time varying model which provides the platform upon which we integrate our multifaceted empirical approaches are also of independent interest. In particular, we provide the general solution for time varying asymmetric GARCH specifications, which is a long standing research topic. This enables us to characterize these models by deriving, first, their multistep ahead predictors, second, the first two time varying unconditional moments, and third, their covariance structure. •We provide new theoretical results on time varying AR-AGARCH models with breaks.•We use tests to estimate the timing of breaks in the mean and volatility dynamics.•We implement these tests to determine changes in the persistence of volatility.•We employ the UEDCC-AGARCH model to analyze the volatility transmission structure.•We show the existence of time varying correlations and shock and volatility spillovers.
ISSN:0927-5398
1879-1727
DOI:10.1016/j.jempfin.2014.08.002