نتایج جستجو برای: MGARCH

تعداد نتایج: 111  

2006
Tae-Hwy Lee Xiangdong Long

Multivariate GARCH (MGARCH) models are usually estimated under multivariate normality. In this paper, for non-elliptically distributed financial returns, we propose copula-based multivariate GARCH (C-MGARCH) model with uncorrelated dependent errors, which are generated through a linear combination of dependent random variables. The dependence structure is controlled by a copula function. Our ne...

2007
Sebastian Kring

In this paper we present a new type of multivariate GARCH model which we call the composed MGARCH and factor composed MGARCH models. We show sufficient conditions for the covariance stationarity of these processes and proof of the invariance of the models under linear combinations, an important property for factor modeling. Furthermore, we introduce an α-stable version of these models and fit a...

Journal: :Computational Statistics & Data Analysis 2010
Kris Boudt Christophe Croux

In empirical work on multivariate financial time series, it is common to postulate a Multivariate GARCH model. We show that the popular Gaussian quasi-maximum likelihood estimator of MGARCH models is very sensitive to outliers in the data. We propose to use robust M-estimators and provide asymptotic theory for M-estimators of MGARCH models. The Monte Carlo study and empirical application docume...

Journal: :Computational Statistics & Data Analysis 2014
Massimiliano Caporin Michael McAleer

During the last 15 years, several Multivariate GARCH (MGARCH) models have appeared in the literature. Recent research has begun to examine MGARCH specifications in terms of their out-of-sample forecasting performance. We provide an empirical comparison of alternative MGARCH models, namely BEKK, DCC, Corrected DCC (cDCC), CCC, OGARCH Exponentially Weighted Moving Average, and covariance shrinkin...

2004
Xiangdong Long Liangjun Su Aman Ullah

The existing parametric multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) model could hardly capture the nonlinearity and the non-normality, which are widely observed in …nancial data. We propose semiparametric conditional covariance (SCC) model to capture the information hidden in the standardized residuals and missed by the parametric MGARCH models. Our two-stage...

Journal: :international economics studies 0
masood dadashi isfahan university of technology, isfahan, iran akbar tavakoli دانشگاه صنعتی اصفهان akbar tavakoli isfahan university of technology, isfahan, iran

â â â  â â â â â  the main purpose of present study is to analyze the relationship between stock and exchange markets in two asian countries, iran and south korea. a monthly time series of stock price and exchange rate are used over the period 2002: 05 - 2012: 03. the data is collected from the central bank of each country and wdi. the calculated stock return and real exchange rate change are u...

Journal: :Studies in Nonlinear Dynamics & Econometrics 2014

2012
Piotr Jaworski Marcin Pitera

We propose a method for defining and measuring the spatial contagion between two financial markets. Next we investigate which from the large family of multivariate GARCH models is the best tool for modeling spatial contagion.

Journal: :Al-Amwal : Jurnal Ekonomi dan Perbankan Syari'ah 2017

1999
Michael S. Haigh Matthew T. Holt

In many studies the assumption is made that traders only encounter one type of price risk. In reality, however, traders are exposed to multiple price risks, and often have several relevant derivative instruments available with which to hedge price uncertainty. In this study, commodity, foreign exchange, and freight futures contracts are analyzed for their effectiveness in reducing price uncerta...

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