Department of Economics and Business Economics

Timo Teräsvirta

Modelling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model

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Modelling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model. / Silvennoinen, Annastiina; Teräsvirta, Timo.

Aarhus : Institut for Økonomi, Aarhus Universitet, 2008.

Research output: ResearchWorking paper

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@techreport{f6c4e7c0cd8b11dcabe4000ea68e967b,
title = "Modelling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model",
abstract = "In this paper we propose a multivariate GARCH model with a time-varying conditionalcorrelation structure. The new Double Smooth Transition Conditional Correlation GARCHmodel extends the Smooth Transition Conditional Correlation GARCH model of Silvennoinenand Ter¨asvirta (2005) by including another variable according to which the correlationschange smoothly between states of constant correlations. A Lagrange multiplier testis derived to test the constancy of correlations against the DSTCC-GARCH model, andanother one to test for another transition in the STCC-GARCH framework. In addition,other specification tests, with the aim of aiding the model building procedure, are considered.Analytical expressions for the test statistics and the required derivatives are provided.The model is applied to a selection of world stock indices, and it is found that time is animportant factor affecting correlations between them.",
keywords = "Multivariate GARCH; Constant conditional correlation; Dynamic conditional",
author = "Annastiina Silvennoinen and Timo Teräsvirta",
year = "2008",
publisher = "Institut for Økonomi, Aarhus Universitet",
type = "WorkingPaper",
institution = "Institut for Økonomi, Aarhus Universitet",

}

RIS

TY - UNPB

T1 - Modelling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model

AU - Silvennoinen,Annastiina

AU - Teräsvirta,Timo

PY - 2008

Y1 - 2008

N2 - In this paper we propose a multivariate GARCH model with a time-varying conditionalcorrelation structure. The new Double Smooth Transition Conditional Correlation GARCHmodel extends the Smooth Transition Conditional Correlation GARCH model of Silvennoinenand Ter¨asvirta (2005) by including another variable according to which the correlationschange smoothly between states of constant correlations. A Lagrange multiplier testis derived to test the constancy of correlations against the DSTCC-GARCH model, andanother one to test for another transition in the STCC-GARCH framework. In addition,other specification tests, with the aim of aiding the model building procedure, are considered.Analytical expressions for the test statistics and the required derivatives are provided.The model is applied to a selection of world stock indices, and it is found that time is animportant factor affecting correlations between them.

AB - In this paper we propose a multivariate GARCH model with a time-varying conditionalcorrelation structure. The new Double Smooth Transition Conditional Correlation GARCHmodel extends the Smooth Transition Conditional Correlation GARCH model of Silvennoinenand Ter¨asvirta (2005) by including another variable according to which the correlationschange smoothly between states of constant correlations. A Lagrange multiplier testis derived to test the constancy of correlations against the DSTCC-GARCH model, andanother one to test for another transition in the STCC-GARCH framework. In addition,other specification tests, with the aim of aiding the model building procedure, are considered.Analytical expressions for the test statistics and the required derivatives are provided.The model is applied to a selection of world stock indices, and it is found that time is animportant factor affecting correlations between them.

KW - Multivariate GARCH; Constant conditional correlation; Dynamic conditional

M3 - Working paper

BT - Modelling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model

PB - Institut for Økonomi, Aarhus Universitet

ER -