In this paper, an adaptive smoothing forecasting approach based on evolutionary spectra as developed by Rao and Shapiro (1970) is applied to the 3003 time series of various types and lengths used in the M3-Competition (Makridakis and Hibon, 2000). Comparisons of out-of-sample forecasts are made...

This article aims to propose a novel hybrid forecasting model involving autoregressive integrated moving average (ARIMA), artificial neural networks (ANNs) and k-means clustering. The single models and k-means clustering are used to build the hybrid forecasting models in different levels of...

This study develops a framework to forecast India's gross domestic product growth on a quarterly frequency from 2004 to 2018. The models, which are based on real and monetary sector descriptions of the Indian economy, are estimated using Bayesian vector autoregression (BVAR) techniques. The real...