Background: In light of the latest global financial crisis and the ongoing sovereign debt crisis, accurate measuring of market losses has become a very current issue. One of the most popular risk measures is Value-at-Risk (VaR). Objectives: Our paper has two main purposes. The first is to test the relative performance of selected GARCH-type models in terms of their ability of delivering volatil...

Beta-t-EGARCH models in which the dynamics of the logarithm of scale are driven by the conditional score are known to exhibit attractive theoretical properties for the t-distribution and general error distribution (GED). The generalized-t includes both as special cases. We derive the information matrix for the generalized-t and show that, when parameterized with the inverse of the tail index, i...

The renewable energies prediction and particularly global radiation forecasting is a challenge studied by a growing number of research teams. This paper proposes an original technique to model the insolation time series based on combining Artificial Neural Network (ANN) and Auto-Regressive and Moving Average (ARMA) model. While ANN by its non-linear nature is effective to predict cloudy days, A...

The 16S rRNA methyltransferase ArmA is a worldwide emerging determinant that confers high-level resistance to most clinically relevant aminoglycosides. We report here the identification and characterization of a multidrug-resistant Salmonella enterica subspecies I.4,12:i:- isolate recovered from chicken meat sampled in a supermarket on February 2009 in La Reunion, a French island in the Indian ...

We introduce the notion of continuous invertibility on a compact set for volatility models driven by a Stochastic Recurrence Equation (SRE). We prove in this context the strong consistency and the asymptotic normality of the M-estimator associated with the Quasi-Likelihood criteria. We recover known results on univariate and multivariate GARCH type models where the estimator coincides with the ...

This article examines the impact of SGX MSCI Taiwan Index Futures on the volatility of the Taiwan stock market. The empirical work is conducted with the use of weekly stock returns from 1995 to 1998 and by applying an expanded EGARCH model. Our findings show that there is no structural change on either the conditional or the unconditional variance after the introduction of index futures contrac...

Empirical Mode Decomposition (EMD), recently proposed by Huang et al. [12], appears to be a novel data analysis method for nonlinear and non-stationary time series. By decomposing a time series into a small number of independent and concretely implicational intrinsic modes based on scale separation, EMD explains the generation of time series data from a novel perspective. This paper presents an...