This paper attempts to assess the Europe-wide systemic risk potential in banking. We employ a bivariate GARCH model to estimate conditional correlations between European bank stock indices. These correlations are used as an indication for the interdependencies amongst the banking business and hence for the systemic risk potential. We employ several tests to assess the development of the systemi...

This paper introduces new classes of bivariate time series models being useful to fit count data time series with a finite range of counts. Motivation comes mainly from the comparison of schemes for monitoring tourism demand, stock data, production and environmental processes. All models are based on the bivariate binomial distribution of Type II. First, a new family of bivariate integer-valued...

We consider extensions of the famous GARCH(1, 1) model where the recursive equation for the volatilities is not specified by a parametric link but by a smooth autoregression function. Our goal is to estimate this function under nonparametric constraints when the volatilities are observed with multiplicative innovation errors. We construct an estimation procedure whose risk attains the usual con...

4 GARCH Models 7 4.1 Basic GARCH Specifications . . . . . . . . . . . . . . . . . . . 8 4.2 Diagnostic Checking . . . . . . . . . . . . . . . . . . . . . . . 11 4.3 Regressors in the Variance Equation . . . . . . . . . . . . . . . 12 4.4 The GARCH–M Model . . . . . . . . . . . . . . . . . . . . . . 12 4.5 The Threshold GARCH (TARCH) Model . . . . . . . . . . . . 12 4.6 The Exponential GARCH (EG...

A new multivariate volatility model that belongs to the family of conditional correlation GARCH models is introduced. The equations this contain a multiplicative deterministic component describe long-run movements in and, addition, correlations are deterministically time-varying. Parameters estimated jointly using maximum likelihood. Consistency and asymptotic normality likelihood estimators pr...

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...

We investigate the weak convergence of a non-Gaussian GARCH model together with an application to the pricing of European style options determined using two different stochastic discount factors: the extended Girsanov principle of Elliott and Madan (1998) and the conditional Esscher transform. Applying these changes of measure to asymmetric GARCH models sampled at increasing frequencies, we obt...