In the last few decades many methods have become available for forecasting. As always, when alternatives exist, choices need to be made so that an appropriate forecasting method can be selected and used for the specific ...

The ultimate test of any forecast is whether or not it is capable of predicting future events accurately. Planners and decision makers have a wide choice of ways to forecast, ranging from purely intuitive or judgemental ...

An altemative to using a single forecasting method is to average the forecasts obtained from several methods. In this paper we investigate empirically the impact of the number and choice of forecasting methods on the ...

The priests of Delfphi have not been alone in providing forecasts for a price. Since the dawn of civilization, a great many fortune tellers, soothsayers, wizards, augurs and astrologers have sought to fulfil the human need ...

Aggregating information by combining forecasts from two or more forecasting methods is an alternative to using just a single method. In this paper we provide extensive empirical results showing that combined forecasts ...

This special section aims to demonstrate the limited predictability and high level of uncertainty in practically all important areas of our lives, and the implications of this. It summarizes the huge body of solid empirical ...

This paper describes an empirical investigation aimed at measuring the effect of different initial values and loss functions (both symmetric and asymmetric) on the post-sample forecasting accuracy. The 1001 series of the ...

Forecasts are crucial for practically all economic and business decisions. However, there is a mounting body of empirical evidence showing that accurate forecasting in the economic and business world is usually not possible. ...

The origins of forecasting can be traced back to the beginning of human civilization with attempts to predict the weather, although forecasting as a field first appeared in the 1940s and attracted more followers from the ...

The origins of forecasting can be traced back to the beginning of human civilization with attempts to predict the weather, although forecasting as a field first appeared in the 1940s and attracted more followers from the ...

Long-term predictions are indispensable for planning and strategy. Yet little is known about their value, their limitations or the most appropriate way of making and using them. This paper examines these issues and proposes ...

First i would like to thank the commentators for their excellent and well thought comments on my paper. I believe that there is little disagrement between their views and mine. All commentators, with the possible exception ...

This paper examines a major area of statistics: the application of time series analysis to forecasting, particularly as it applies to the areas of business and economics. This area is unusual in the social sciences in that ...

This conclusion aims to summarize the major issues surrounding forecasting, as well as the extensive empirical evidence proving our inability to accurately predict the future. In addition, it discusses our resistance to ...

Forecasting has a long history. An understanding of such history coupled with the study of the empirical evidence can provide invaluable information for improving the accuracy and usefulness of predictions. Statistical ...

Available approaches to statistical forecasting suffer from several deficiencies (problems) that render their predictions for real-world economic/business series inappropriate. In this paper I illustrate such deficiencies, ...

The SIBYL/RUNNER interactive forecasting system is a comprehensive package of time-shared computer programs that seek to handle four essential forecasting functions. The first is screening alternative forecasting techniques ...

Long-term predictions are indispensable for planning and strategy. Yet little is known about their value, their limitations or the most appropriate way of making and using them. This paper examines these issues and proposes ...

This paper proposes a new approach to time series forecasting based upon three premises. First, a model is selected not by how well it fits historical data but on its ability to accurately predict out-of-sample actual data. ...

First, it is practically oriented. It avoids theoretical, and mathematical discussions. It directly gets into how to use it, when to use it, what it is used for, and what resources are required of it. It includes many ...