Volatility transmission between international stock markets

2007

Statistical Learning Algorithms to Forecast the Equity Risk Premium in the European Union

2018

With the explosion of “Big Data”, the application of statistical learning models has become popular in multiple scientific areas as well as in marketing, finance or other business disciplines. Nonetheless, there is not yet an abundant literature that covers the application of these learning algorithms to forecast the equity risk premium. In this paper we investigate whether Classification and Regression Trees (CART) algorithms and several ensemble methods, such as bagging, random forests and boosting, improve traditional parametric models to forecast the equity risk premium. In particular, we work with European Monetary Union data for a period that spans from the EMU foundation at the begin…

Forecasting the Equity Risk Premium in the European Monetary Union

2018

This article examines the performance of several variables that could be good predictors of the equity risk premium in the European Monetary Union for a period that spans from 2000 to 2015. In-sample, technical indicators display predictive power, matching or exceeding that of traditional economic forecasting variables. We also find consistent results in the fact that combining information from technical and economic variables improves equity risk premium forecasts, compared to using these variables alone. Nevertheless, out-of-sample exercises do not confirm in-sample results. Economic predictors show stronger out-of-sample forecasting ability than technical indicators, and apart from volum…