We examine the forecasting performance of parametric and nonparametric models based on a training-validation sample approach and the use of rolling short-term forecasts to compute root mean-squared errors,We find that the performance of these models is better than that of the naıve, no-change...

In this analysis of the risk and return of stocks in global markets, we build a reasonably large number of stock selection models and create optimized portfolios to outperform a global benchmark. We apply robust regression techniques include variable selection method like LASSO and LAR...

In this paper I propose a novel optimal linear filter for smoothing, trend and signal extraction for time series with a unit root. The filter is based on the Singular Spectrum Analysis (SSA) methodology, takes the form of a particular moving average and is different from other linear filters...