The forecasts accuracy evaluation became a constant preoccupation of specialists in forecasting, because of the failure of predictions that caused the actual economic crisis. The objective of this research is to model and predict some economic variables corresponding too few macroeconomic blocks for Romanian economy. The forecast method is represented by econometric models. Moreover, the accura...

Modeling price risks is crucial for economic decision making in energy markets. Besides the risk of a single price, dependence structure multiple prices often relevant. We therefore propose generic and easy-to-implement method creating multivariate probabilistic forecasts based on univariate point day-ahead electricity prices. While each forecast refers to one day's 24 hours, distribution model...

After the so-called Asia crisis in the summer of 1997 the nancial markets were shaken by increased volatility transmission around the world. Therefore, in this paper we will analyse the daily exchange rates in New York, Germany, and Japan for the period of 2 years (June 21, 1996 to June 22, 1998). We estimate a VAR-GARCH in mean model and estimate the multivariate volatility e ects between the ...

This paper uses a multivariate vector error-correction generalized autoregressive conditional heteroscedasticity model to investigate the effect of British grain prices on their Irish equivalents. We find that in the long run the law of one price holds and in the short run the model captures the salient features of Irish grain prices. The model is used to compute rolling forecasts of the condit...

Heat waves have been responsible for more fatalities in Europe over the past decades than any other extreme weather event. However, temperature-related illnesses and deaths are largely preventable. Reliable sub-seasonal-to-seasonal (S2S) climate forecasts of extreme temperatures could allow for better short-to-medium-term resource management within heat-health action plans, to protect vulnerabl...

This study forecasts trading signals of the Australian All Ordinary Index (AORD), one day ahead. These forecasts were based on the current day’s relative return of the Close price of the US S&P 500 Index, the UK FTSE 100 Index, French CAC 40 Index and German DAX Index as well as the AORD. The forecasting techniques examined were feedforward and probabilistic neural networks. Performance of the ...

We examine the forecasting performance of a range of time-series models of the daily US effective federal funds (FF) rate recently proposed in the literature. We find that: (i) most of the models and predictor variables considered produce satisfactory oneday-ahead forecasts of the FF rate; (ii) the best forecasting model is a simple univariate model where the future FF rate is forecast using th...