multivariate GARCH
Asymptotic Theory of General Multivariate GARCH Models
... of GARCH models are usually estimated by the quasi-maximum likelihood esti- mator ...of multivariate models a ...the multivariate GARCH models is far from coherent since many algorithms on the ...
142
Volatility Integration of Global Stock Markets with the Malaysian Stock Market: A Multivariate GARCH Approach
... using GARCH-BEKK, CCC and DCC models also discovered that Japan was most influenced by spillover effects from the US during the GFC period, and the impact are likely to transmit to East Asian countries via ...
36
Mortgage Lending and the Great moderation: a multivariate GARCH Approach
... Importantly, we test these relations in variances rather than levels. The Great Moderation was a reduction in the variance of output (denoted Y), but also of the financial-sector variables that possibly caused it (Bean, ...
32
The Role of Credit in Great Moderation: a Multivariate GARCH Approach
... a multivariate GARCH ...for multivariate GARCH models we choose an unrestricted bivariate VAR-BEKK model (Engle and Kroner, 1995), appropriate for the computation of conditional variances and ...
36
Estimating multivariate GARCH and stochastic correlation models equation by equation
... the multivariate extension of the concepts and models developed for univariate ...of multivariate GARCH (MGARCH) models, the most popular seem to be the Constant Conditional Correlations (CCC) model ...
49
An Asymmetric Block Dynamic Conditional Correlation Multivariate GARCH Model
... the GARCH model of Bollerslev (1986) has been extended to several classes of multivariate GARCH models (see Bauwens, Laurent and Rombouts ...(2006)). GARCH itself has come a long way since ...
21
Model and distribution uncertainty in multivariate GARCH estimation: a Monte Carlo analysis
... Multivariate GARCH models are in principle able to accommodate the features of the dynamic conditional correlations processes, although with the drawback, when the number of financial returns series ...
26
Assessing portfolio market risk in the BRICS economies: use of multivariate GARCH models
... using multivariate GARCH models (Lee, Chiou & Lin (2006), Hsu Ku & Wang (2008), Santo et ...on GARCH models and for portfolio ...using multivariate GARCH models and accounting ...
45
QML estimation of a class of multivariate GARCH models without moment conditions on the observed process
... We establish the strong consistency and asymptotic normality of the quasi-maximum likelihood estimator of the parameters of a class of multi- variate GARCH processes. The conditions are mild and coincide with the ...
29
Measuring spot variance spillovers when (co)variances are time varying the case of multivariate GARCH models
... In this paper, we propose such an approach. We adopt the ideas of Diebold and Yilmaz (2009, 2012) and construct variance spillover indices that are updated with time-t information. To this end, we build on ...
43
Time-varying Return and Volatility Spillover among EAGLEs Stock Markets: A Multivariate GARCH Analysis
... uses multivariate GARCH model to explore the volatility spillover dynamics, this paper applies a multivariate GARCH dy- namic conditional correlation (DCC) as well as BEEK ...
20
Volatility in High Frequency Intensive Care Mortality Time Series: Application of Univariate and Multivariate GARCH Models
... )), GARCH (Generalised Autoregressive Conditional Heteroscedasticity, lags ( p , q ...utilising multivariate GARCH ...power GARCH model (lags (1, 1)) with t distribution (degrees-of- freedom, ...
27
Semiparametric Estimation of Multivariate GARCH Models
... of multivariate GARCH models, ...univariate GARCH models for the conditional variances in the first step and then the esti- mation of the conditional covariances in the second ...
7
Modeling Covariance Breakdowns in Multivariate GARCH
... This paper proposes a flexible way of modeling dynamic heterogeneous covariance break- downs in multivariate GARCH (MGARCH) models. During periods of normal market activ- ity, volatility dynamics are ...
45
Tests for sphericity in multivariate garch models
... Tests for sphericity in multivariate garch models Francq, Christian and Jiménez Gamero, Maria Dolores and Meintanis, Simos.[r] ...
42
Testing the CAPM for the Brazilian Stock Market Using Multivariate GARCH between 1995 and 2012
... The betas estimated with MGARCH are called conditional betas. The model is known DCC (Dynamic Conditional Correlation)-MGARCH because the correlations are time-varying. For each asset is estimated a univariate model, but ...
23
Variance targeting estimation of multivariate GARCH models
... literature, multivariate conditionally het- eroskedastic (GARCH) models are notoriously difficult to ...univariate GARCH setting - can be difficult to ...univariate GARCH(p, q) by Kristensen ...
36
Uncovering equity market contagion among BRICS countries: an application of the multivariate GARCH model
... As the focus of this paper is on the dynamic conditional correlation obtained in the third step of the VAR-DCC-GARCH model, Figures 6 to 9 display the dynamic conditional correlation between South Africa and each ...
26
A multivariate GARCH model for the non-normal behaviour of financial assets
... 150 0.0000 0.3000 0.5231 AGDCC_2 AGDCC_3 1 The p-values were calculated using three different estimators for the conditional variance-covariance matrix: AGDCC 1 first Asymmetric-Generali[r] ...
158
Market Interactions in Gold and Stock Markets: Evidences from Saudi Arabia
... This section briefly reviews a few important works carried out in the domain of gold as an asset class. The methods adopted are highlighted. Contuk et al. (2013) while studying the effect of fluctuation of gold price on ...
10