In this paper we investigate whether and how far density forecasts sensibly can be combined to produce a “better” pooled density forecast. In so doing we bring together two important but hitherto largely unrelated areas of the forecasting literature in economics, density forecasting and forecast combination. We provide simple Bayesian methods of pooling information across alternative density fo...

Forecasts of economic time series are often evaluated according to their accuracy as measured by either quantitativeprecision or qualitative reliability. We argue that consumers purchase forecasts for the potentialutility gains from utilizing them, not for theiraccuracy. Using Monte Carlo techniques to incorporate the temporal heteroskedasticity inherent in asset returns,the expected utility of...

Conditions under which monthly rainfall forecasts translate into monthly runoff predictions that could support water resources planning and management activities were investigated on a small watershed in central Oklahoma. Runoff response to rainfall forecasts was simulated using the hydrologic model SWAT. Eighteen scenarios were examined that represented combinations of wet, average, and dry an...

This document is another installment in a series of near real-time weekly influenza forecasts made during the 2012-2013 influenza season. Here we present some of the results of forecasts initiated following assimilation of observations for Week 52 (i.e. the forecast begins December 30, 2012) for municipalities in the United States. The forecasts were made on January 4, 2013. Results from foreca...

We present here an original work that uses machine learning techniques to combine time series forecasts. In this proposal, a machine learning technique uses features of the series at hand to define adequate weights for the individual forecasting methods being combined. The combined forecasts are the weighted average of the forecasts provided by the individual methods. In order to evaluate this ...

Predictions about the future are commonly evaluated through statistical tests. As shown by recent literature, many known tests subject to adverse selection problems and cannot discriminate between forecasters who competent uninformed but predict strategically. We consider a framework where forecasters' predictions must be consistent with paradigm , set of candidate probability laws for stochast...

Skillful seasonal streamflow forecasts obtained from climate and land surface conditions could significantly improve water and energy management. Since climate forecasts are updated on a monthly basis, we evaluate the potential in developing operational monthly streamflow forecasts on a continuous basis throughout the year. Further, basins in the rainfall–runoff regime critically depend on the ...

We study a matched sample of individual stock market forecasts consisting of both qualitative and quantitative forecasts. This allows us to test for the quality of forecast quantification methods by comparing quantified qualitative forecasts with actual quantitative forecasts. Focusing mainly on the widely used quantification framework advocated by Carlson and Parkin (1975), the so-called “prob...

Independent forecasts obtained from different temporal aggregates of a given time series may not be mutually consistent. State-of-the art forecasting methods usually apply adjustments on the individual level forecasts to satisfy the aggregation constraints. These adjustments require the estimation of the covariance between the individual forecast errors at all aggregation levels. In order to ke...