Short-term traffic forecasting aims to provide more reliable travel information service, so as to assist people in making more reasonable travel decisions. With the increasing availability of traffic data along with the development of communication technology, both the capability and accuracy of travel time forecasting have been significantly enhanced in real-time conditions and a great number ...

In this paper an ANN model is developed to forecast the monthly inflation of Bangladesh as a function of its own previous value. The model selects a feed-forward backpropagation ANN with two inputs, one hidden layer with five hidden neurons and one output as the optimum network. The model is tested with actual time series data of inflation in case of Bangladesh and forecast evaluation criteria....

This paper studies forecasts when the forecast loss function is asymmetric, using Australian unemployment rates as an example. We focus on simple univariate models including autoregressive models and self-exciting threshold autoregressive models and we employ the same asymmetric quadratic loss function that is used for forecast evaluation at the model selection, model estimation and forecast co...

We provide a summary updated guide for the construction, use and evaluation of leading indicators, and an assessment of the most relevant recent developments in this field of economic forecasting. To begin with, we analyze the problem of selecting a target coincident variable for the leading indicators, which requires coincident indicator selection, construction of composite coincident indexes,...

Stock price forecasting models with lower Mean Squared Error (MSE) are more “welcome" than those who have higher MSE. However, this “welcome" may disappear when lower MSE leads to an unexpected loss whereas higher MSE leads to a positive profit in a practical investment. The reason is that MSE aims to evaluate models in the view of “accuracy", which has nothing to do with profit. We therefore p...

The validity of previous findings that dynamic factor models are useful for macroeconomic forecasting is of great importance for subsequent studies which use these models not only as a starting point for further developments but also as a benchmark for the evaluation of the forecasting performance of these further developments. Reanalyzing a standard macroeconomic dataset, we do not find any ev...