The Advanced Regional Prediction System (ARPS) three-dimensional variational (3DVAR) system is enhanced to include the analysis of radar-derived refractivity measurements. These refractivity data are most sensitive to atmospheric moisture content and provide high-resolution information on near-surface moisture that is important to convective initiation (CI) and precipitation forecasting. Observ...

In the last decade, increases in fire activity and suppression expenditures have caused budgetary problems for federal land management agencies. Spatial forecasts of upcoming fire activity and costs have the potential to help reduce expenditures, and increase the efficiency of suppression efforts, by enabling them to focus resources where they have the greatest effect. In this paper, we present...

The information contained in one model’s forecast compared to that in another can be assessed from a regression of actual values on predicted values from the hvo models. We do this for forecasts of real GNP growth rates for different pairs of models. The models include a structural model (the Fair (1976) model), uariour versions of the vector autoregressive (VAR) model, and various versions of ...

We specify a class of non-linear and non-Gaussian models for which we estimate and forecast the conditional distributions with daily frequency. We use these forecasts to calculate VaR measures for three different equity markets (US, GB and Japan). These forecasts are evaluated on the basis of different statistical performance measures as well as on the basis of their economic costs that go alon...

Age-sex-specific population forecasts are derived through stochastic population renewal using forecasts of mortality, fertility and net migration. Functional data models with time series coefficients are used to model age-specific mortality and fertility rates. As detailed migration data are lacking, net migration by age and sex is estimated as the difference between historic annual population ...

Age-sex-specific population forecasts are derived through stochastic population renewal using forecasts of mortality, fertility and net migration. Functional data models with time series coefficients are used to model age-specific mortality and fertility rates. As detailed migration data are lacking, net migration by age and sex is estimated as the difference between historic annual population ...

abstract: with regard to the basel committee’s emphasis on the necessity of using 10-day value-at-risk (var) internal models in order to determine minimum market risk capital requirements, and downsides of the square-root-of-time rule, our purpose is to produce more accurate forecasts of the multi-period var using sixteen models for three stock indices, the tepix, nasdaq, and ftse. the results,...

We provide a new perspective on disagreement in in‡ation expectations by examining the full probability distributions of UK consumer in‡ation forecasts based on an adaptive bootstrap multimodality test. Furthermore, we compare the in‡ation forecasts of the Bank of England’s Monetary Policy Committee (MPC) with those of UK consumers, for which we use data from the 2001-2007 February GfK NOP cons...

This paper proposes a Bayesian procedure for combining forecasts from multivariate forecasting models, e.g. VAR models. Standard applications of Bayesian model averaging suffer from a basic difficulty in this context, when additional variables are included and modelled the connection between the overall measure of fit for the model and the expected forecasting performance for the variables of i...

The variance of a portfolio can be forecasted using a single index model or the covariance matrix of the portfolio. Using univariate and multivariate conditional volatility models, this paper evaluates the performance of the single index and portfolio models in forecasting Value-at-Risk (VaR) thresholds of a portfolio. The LR tests of unconditional coverage, independence and conditional coverag...