Purpose – The purpose of this paper is to associate a probabilistic confidence with the stock market interval forecasts obtained with the interval least squares (ILS) algorithm. The term probabilistic confidence in this paper means the probability of a point observation that will fall in the...

Purpose – The purpose of this paper is to associate a probabilistic confidence with the stock market interval forecasts obtained with the interval least squares (ILS) algorithm. The term probabilistic confidence in this paper means the probability of a point observation that will fall in the...

Purpose – The objective of this paper is to develop a model that can predict financial distress amongst public listed companies in Malaysia using the logistic regression analysis. Design/methodology/approach – The logistic regression analysis used in this paper is geared towards developing a...

This paper investigates the impact of the timeliness of information releases and data vintage variation on economic forecast quality. Specifically, using a set of 63 key US economic series, we provide a concise measure of the forecast accuracy associated with use of economic activity indices...

Is the imprecision of economic forecasts due to the judgements of biased decision makers? This study explores decision making among expert forecasters in Sweden using semistructured interviews. The results indicate that forecasters' decision processes are characterised by intuitive, as well as...

In this work we consider the forecasting of macroeconomic variables during an economic crisis. The focus is on a specific class of models, the so-called single hidden-layer feed-forward autoregressive neural network models. What makes these models interesting in the present context is the fact...

Purpose – The purpose of this paper is to evaluate the performance of six types of policy rules applied for Indonesia, using monthly data spanning January 1980 to December 2008. Design/methodology/approach – This paper uses deterministic simulations on a small macro model and evaluates the...

A new method of assessing the comparative quality of forecasting models is introduced. This method focuses on the quality of forecasting models over a set of series (cf. the traditionally adopted series-by-series approach)–with a forecasting model that produces good forecasts over a series set...

This work proposes a new forecasting model to analyse the economic development of Sichuan province of China. The model, which introduces the concept of diversity, is based on an improvement of the -GMDH algorithm. The new method, called D-GMDH, is compared with two ensemble approaches which are...

A structural break is viewed as a permanent change in the parameter vector of a model. Using taxonomies of all sources of forecast errors for both conditional mean and conditional variance processes, we consider the impacts of breaks and their relevance in forecasting models: (a) where the...