Stock return predictability in the spanish stock market : a conventional and an alternative methodology

We carry out an empirical analysis on the Spanish Stock Market from July 2003 to June 2015, with an aim to examine whether the monthly returns can be predicted. We test the return predictability of the Spanish Stock Market through two different methodologies. First, we use a linear estimator, the FGLS and, secondly, we use a non-parametric approach, the RE-EM tree. The latter is tested in-sample and out-of-sample. We use a total of nine predictors, two of which are non-traditional variables: gold and oil returns. We conclude that macroeconomic variables are more relevant forecasting monthly returns than the business performance (ratios) predictors. We also find evidence in favour of in-sample return predictability. Although we find a 56.7% of success forecasting the sign of the real returns in the out-of-sample period through the RE-EM tree, it may not be enough to outperform the market once all the transaction costs are discounted. We also find that the return predictability is heterogeneous among different sectors