the other periods. Croston's method is a widely used procedure for intermittent demand forecasting. However, it is an ad …

assumed to be Gaussian, the resulting prediction distribution may have an infinite variance beyond a certain forecasting … approximation causes no serious problems for parameter estimation or for forecasting one or two steps ahead. However, for longer …. The performance of the Gaussian approximation is compared with those of two lognormal models for short-term forecasting …

estimator for forecasting time series, with a special attention to GARCH and ACD models. The local large sample properties of … suboptimal for forecasting purposes. The paper proposes the use of a class of shrinkage estimators that includes the Ridge …-daily financial durations forecasting application. The empirical application shows that an appropriate shrinkage forecasting …

This paper assesses the performance of volatility forecasting using focused selection and combination strategies to … include relevant explanatory variables in the forecasting model. The focused selection/combination strategies consist of … BIC. The methodology is applied to a daily recursive 1--step ahead value--at--risk (VaR) forecasting exercise of 4 widely …

We propose a parametric state space model with accompanying estimation and forecasting framework that combines long … process, the model consistently belongs to the 10% Model Confidence Set when considering out-of-sample forecasting performance … as the only one among four competing dynamic models for all forecasting horizons when applied to high frequency stock …

Institute of Forecasters (Journal of Forecasting 1982-1985; International Journal of Forecasting 1985-2005). During this period …, over one third of all papers published in these journals concerned time series forecasting. We also review highly … influential works on time series forecasting that have been published elsewhere during this period. Enormous progress has been …

The GARCH(1,1) model and its extensions have become a standard econometric tool for modeling volatility dynamics of … financial returns and port-folio risk. In this paper, we propose an adjustment of GARCH implied conditional value-at-risk and … means of conditional moments of simulated bivariate standardized copula distributions. We conduct in-sample forecasting …

Using unobservable conditional variance as measure, latent-variable approaches, such as GARCH and stochastic … propose extensions to explicitly account for these properties and assess their relevance when modeling and forecasting … distributional assumption for residuals plays a crucial role in density forecasting. …