The main problem in the combination of volatility forecasts is that the volatility cannot be directly observed and hence loss functions such as the MSFE cannot be directly used unless a suitable proxy of the conditional variance is defined. A common approach is to use the squared returns but...

In this paper we propose an approach to modelling non-linear conditionally heteroscedastic time series characterised by asymmetries in both the conditional mean and variance. This is achieved by combining a TAR model for the conditional mean with a Changing Parameters Volatility (CPV) model for...

This paper proposes a novel approach to the combination of conditional covariance matrix forecasts based on the use of the Generalized Method of Moments (GMM). It is shown how the procedure can be generalized to deal with large dimensional systems by means of a two-step strategy. The finite...

A novel approach to the combination of volatility forecasts is discussed. The proposed procedure makes use of the generalized method of moments (GMM) for estimating the combination weights. The asymptotic properties of the GMM estimator are derived while its finite sample properties are assessed...

In this paper we propose the use of a threshold autoregressive conditional heteroakedastic model to examine the dynamic asymmetries in the unemployment rate time series. A simple extension that allows to account for seasonal variation is also considered. The model performance and the effect of...

The paper presents a competing-risks approach for investigating the determinants of corporate financial distress. In particular a comparative analysis of three European markets - France, Italy and Spain – is performed in order to find out the similarities and the differences in the...

In this paper we develop statistical models for bankruptcy prediction of Italian firms in the limited liability sector, using annual balance sheet information. Several issues involved in default risk analysis are investigated, such as the structure of the data-base, the sampling procedure and...

Modeling crude oil volatility is of substantial interest for both energy researchers and policy makers. Many authors emphasize the link between this volatility and some exogenous economic variables. This paper aims to investigate the impact of the U.S. Federal Reserve monetary policy on crude...

Tools and approaches are provided for nonlinear time series modelling in econometrics. A wide range of topics is covered, including probabilistic properties, statistical inference and computational methods. The focus is on the applications but the ideas of the mathematical arguments are also...