The recently proposed class of MixN-GARCH models, which couple a mixed normal distributional structure with linked GARCH-type dynamics, has been shown to offer a plausible decomposition of the contributions to volatility, as well as admirable out-of-sample forecasting performance, for financial...

Empirically, we show that the proportion of stocks exhibiting conditional heteroscedastic residuals, is high. We suggested to use the market model with GARCH(1,1) residuals in order to describe daily stock returns and derived a test statistics for the null hypothesis of no abnormal returns,...

We present a multivariate, non-parametric technique for constructing reliable daily VaR predictions for individual assets belonging to a common equity market segment, which takes also into account the possible dependence structure between the assets and is still computationally feasible in large...

A small strand of recent literature is occupied with identifying simultaneity in multipleequation systems through autoregressive conditional heteroscedasticity. Since thisapproach assumes that the structural innovations are uncorrelated, any contemporaneousconnection of the endogenous variables...

In recent years, support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a...

This paper offers a new method for estimation and forecasting of the linear and nonlinear time series when the stationarity assumption is violated. Our general local parametric approach particularly applies to general varying-coefficient parametric models, such as AR or GARCH, whose coefficients...

A huge body of empirical and theoretical literature has emerged on the relationship between foreign exchange (FX) uncertainty and international trade. Empirical findings about the impact of FX uncertainty on trade figures are at best weak and often ambiguous with respect to its direction. Almost...

The present paper embarks on an analysis of interactions between the US and Euroland in the capital, foreign exchange, money and stock markets from 1994 until 2006. Considering influences on financial market volatility, the estimations are carried out in multivariate EGARCH models using...

The present paper analyses interactions between the foreign exchange, money and stock markets in Asian Pacific countries from 1999 till 2006. Considering influences on financial market volatility, the estimations are carried out in multivariate EGARCH models using structural residuals. This...

This paper proposes a novel approach to the combination of conditional covariancematrix forecasts based on the use of the Generalized Method of Moments (GMM). Itis shown how the procedure can be generalized to deal with large dimensional systemsby means of a two-step strategy. The finite sample...