نتایج جستجو برای: multivariate garch

تعداد نتایج: 120385  

Journal: :Journal of Applied Econometrics 2006

Journal: :Journal of Time Series Econometrics 2022

Abstract For large multivariate models of generalized autoregressive conditional heteroskedasticity (GARCH), it is important to reduce the number parameters cope with ‘curse dimensionality’. Recently, Laurent, Rombouts and Violante (2014 “Multivariate Rotated ARCH Models” Journal Econometrics 179 : 16–30) developed rotated GARCH model, which focuses on for standardized variables. This paper ext...

Journal: :European Journal of Finance 2021

We investigate a solution for the problems related to application of multivariate GARCH models markets with large number stocks by restricting form conditional covariance matrix. The model is factor and uses only six free parameters. One can be interpreted as market component, remaining factors are equal. This allow analytical calculation inverse time-dependence enables determination dynamical ...

2004
Matteo Manera Michael McAleer Margherita Grasso

This paper estimates the dynamic conditional correlations in the returns on Tapis oil spot and onemonth forward prices for the period 2 June 1992 to 16 January 2004, using recently developed multivariate conditional volatility models, namely the Constant Conditional Correlation Multivariate GARCH (CCCMGARCH) model of Bollerslev [1990], Vector Autoregressive Moving Average – GARCH (VARMAGARCH) m...

2004
Jeroen V.K. Rombouts Marno Verbeek

In this paper we examine the usefulness of multivariate semi-parametric GARCH models for portfolio selection under a Value-at-Risk (VaR) constraint. First, we specify and estimate several alternative multivariate GARCH models for daily returns on the S&P 500 and Nasdaq indexes. Examining the within sample VaRs of a set of given portfolios shows that the semi-parametric model performs uniformly ...

2014
Lucia Alessi Matteo Barigozzi Marco Capasso Giorgio Calzolari Mario Forni Marc Hallin Daniel Peña Esther Ruiz

We propose a new model for volatility forecasting which combines the Generalized Dynamic Factor Model (GDFM) and the GARCH model. The GDFM, applied to a large number of series, captures the multivariate information and disentangles the common and the idiosyncratic part of each series of returns. In this financial analysis, both these components are modeled as a GARCH. We compare GDFM+GARCH and ...

2005
Giovanni De Luca Marc G. Genton Nicola Loperfido

Empirical research on European stock markets has shown that they behave differently according to the performance of the leading financial market identified as the US market. A positive sign is viewed as good news in the international financial markets, a negative sign means, conversely, bad news. As a result, we assume that European stock market returns are affected by endogenous and exogenous ...

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