Volatility linkages across three major equity markets: A financial arbitrage approach

Cifarelli, Giulio; Paladino, Giovanna

doi:10.1016/j.jimonfin.2005.01.005

Cited by 24 publications

(14 citation statements)

References 36 publications

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“…Relative to other frameworks Cifarelli and Paladino (2005) suggest that multivariate GARCH models are more difficult to implement than vector autorregresive (VAR) models, but on the other hand, provide the required information about the evolution of volatility and its transmission.…”

Section: Methodsmentioning

confidence: 99%

Asymmetric variance and spillover effects

Marcelo

Quirós

2008

Journal of International Financial Markets, Institutions and Mo

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Section: Methodsmentioning

confidence: 99%

Asymmetric variance and spillover effects

Marcelo

Quirós

2008

Journal of International Financial Markets, Institutions and Mo

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“…It follows that BEKK-GARCH (1,1) type models (Cifarelli and Paladino 2005;Qiao et al 2008) have been commonly used to examine the timevarying correlations/volatility spillovers phenomenon. 4 It is generally recognized that BEKK models involve somewhat heavy computations and suffer from a high dimension problem.…”

Section: Literature On Comovement and Smooth Transitionmentioning

confidence: 99%

Comovements between Chinese and global stock markets: evidence from aggregate and sectoral data

Chiang

Lao

Xue³

2015

Rev Quant Finan Acc

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This paper investigates the dynamic correlations between Chinese stock returns and global markets at both the market and sectoral levels. Statistics suggest that stockreturn correlations across markets are time-varying and display structural breaks. An upward shift in stock return correlations is associated with China's adoption of a higher degree of financial liberalization. The evidence indicates that the stock returns of the financial sector exhibit the highest correlation across countries among 10 sectors. Low correlations are present in the Health Care, Telecommunications, and Utilities sectors. The correlations are closely tied to geographic location: the correlation with Hong Kong is the highest, followed by South Korea, Japan, Europe and the US. The time-series stock-return correlations are positively correlated with the conditional variance and variance premiums.

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“…A core advantage of these models is their empirical insight on the interaction of conditional variances and covariance of the underlying asset series. Despite certain specification complexities compared to the vector autoregressive (VAR) models, the multivariate GARCH structures provide useful information on the dynamic evolution and implications of return volatilities (Cifarelli and Paladino, 2005). The VECH model (Bollerslev et al, 1988) and the BEKK model (Engle and Kroner, 1995) 1 have been among the most popular multivariate GARCH models.…”

Section: Modelling Dynamics In the Correlationsmentioning

confidence: 99%