We propose a new semiparametric observation-driven volatility model where the form of the error density directly influences the volatility dynamics. This feature distinguishes our model from standard semiparametric GARCH models. The link between the estimated error density and the volatility...

See also the article 'Mean and bold: on separating merger economies from structural efficiency gains in the drinking water sector' 2010, <I>The Journal of the Operational Research Society</I>, 61, 222-34.<P> The Dutch drinking water sector experienced two drastic changes over the last 10 years. Firstly,...</p></i>

We propose procedures for estimating the time-dependent transition matrices for the general class of finite nonhomogeneous continuous-time semi-Markov processes. We prove the existence and uniqueness of solutions for the system of Volterra integral equations defining the transition matrices,...

An intensive and still growing body of research focuses on estimating a portfolio’s Value-at-Risk.Depending on both the degree of non-linearity of the instruments comprised in the portfolio and thewillingness to make restrictive assumptions on the underlying statistical distributions, a...

A growing number of empirical studies provides evidence that dynamic properties of macroeconomic time series have been changing over time. Model-based procedures for the measurement of business cycles should therefore allow model parameters to adapt over time. In this paper the time dependencies...

This paper proposes a new set of transformed polynomial functions that provide a flexible setting for nonlinear autoregressive modeling of the conditional mean while at the same time ensuring the strict stationarity, ergodicity, fading memory and existence of moments of the implied stochastic...

In this paper we perform a meta-analysis on empirical estimates of the impact between investment and uncertainty. Since the outcomes of primary studies are largely incomparable with respect to the magnitude of the effect, our analysis focuses on the direction and statistical significance of the...

We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...

In this article we introduce a new class of test statistics designed to detect the occurrence of abnormal observations. It derives from the joint distribution of moment- and quantile-based estimators of power variation sigma^r, under the assumption of a normal distribution for the underlying...

Market share models for weekly store-level data are useful to understand competitive structures by delivering own and cross price elasticities. These models can however not be used to examine which brands lose share to which brands during a specificperiod of time. It is for this purpose that we...