We reveal that in the estimation of univariate GARCH or multivariate generalized orthogonal GARCH (GO-GARCH) models, maximizing the likelihood is equivalent to making the standardized residuals as independent as possible. Based on that, we propose three factor GARCH models in the framework of GO-GARCH: independent-factor GARCH exploits factors that are statistically as independent as possible; ...

Abstract This article aims to examine the transmission of return and volatility spillover from banking industry other industries in Pakistan. The study uses daily stock prices 2005 2018 financial non‐financial sectors listed at Pakistan exchange. KSE‐100 index is used as a basis for selection he companies. ARMA‐GARCH mean model measure spillover. time‐varying conditional correlation asymmetric ...

To capture the missed information in the standardized errors by parametric multivariate generalized autoregressive conditional heteroskedasticity (MV-GARCH) model, we propose a new semiparametric MV-GARCH (SM-GARCH) model. This SM-GARCH model is a twostep model: firstly estimating parametric MV-GARCH model, then using nonparametric skills to model the conditional covariance matrix of the standa...

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...

This paper proposes a new clustered correlation multivariate GARCH model (CCMGARCH) that allows conditional correlations to form clusters. This model can generalize the time-varying correlation structure in Tse and Tsui (2002) by determining a natural grouping of the correlations among the series. To estimate the proposed model, we adopt Markov Chain Monte Carlo methods. Two efficient sampling ...

The paper investigates persistence, returns and volatility spillovers from the bitcoin market to gold silver markets using daily datasets January 2, 2018 July 31, 2020 by employing fractional persistence framework. results show strong price with posing highest while poses lowest persistence. of multivariate GARCH modelling, CCC-VARMA-GARCH model other lower variants indicate impossibility spill...

This paper investigates the performance of quasi maximum likelihood (QML) and nonlinear least squares (NLS) estimation applied to temporally aggregated GARCH models. Since these are known to be only weak GARCH, the conditional variance of the aggregated process is in general not known. Thus, one major condition that is often used in proving the consistency of QML, the correct specification of t...

H igh price volatility and the risk are the main features of commodity markets. One way to reduce this risk is to apply the hedging policy by future contracts. In this regard, in this paper, we will calculate the optimal hedging ratios for OPEC oil. In this study, besides the multivariate GARCH models, for the first time we use conditional copula models for modelling dependence struc...

This paper derives the statistical properties of a two-step approach to estimating multivariate rotated GARCH-BEKK (RBEKK) models. From definition RBEKK, unconditional covariance matrix is estimated in first step rotate observed variables order have identity for its sample matrix. In second step, remaining parameters are by maximizing quasi-log-likelihood function. For this quasi-maximum likeli...