We investigate forecast performance of artificial neural network models using Ashley, et al. (1980) and employ neural network nonlinearity test proposed by Lee, et al. (1993) to find possible existence of business cycle asymmetries in Canada, France, Japan, UK, and USA real GDP growth rates. Our...

We search for time-varying predictable components in monthly excess stock index returns over the risk free rates in the G7 countries. The predictable components provide an estimate of the expected excess returns. Our unobserved components model improves on Conrad and Kaul (1988) by taking into...

We investigate business cycle asymmetries in the real GDP of eleven selected Asian economies using nonlinear switching time series models and artificial neural networks. Results based on neural network linearity tests show evidence of business cycle asymmetries in all series. Results based on...

We investigate the possible predictability of firm growth in Taiwan using cross-sectional data of financial factors for the years 1997 and 2003 via principal component analysis. Our results reveal that the 18 financial variables (sales growth rate, total assets, total sales, return on assets,...