This paper builds on the recent debate on the in-sample and out-of-sample predictability of US aggregate returns using a wide range of predictors by providing new evidence for smaller and less market-oriented European countries. We find evidence that macro and technical predictors can...

We investigate whether value-relevant foreign information only gradually dilutes into stock prices of multinational firms worldwide. Using an international sample of firms from 22 developed countries, we find that a portfolio strategy based on firms' foreign sales information yields future...

This paper uses Monte Carlo techniques to assess the loss in terms of forecast accuracy which is incurred when the true DGP exhibits parameter instability which is either overlooked or incorrectly modelled. We find that the loss is considerable when a FCM is estimated instead of the true TVCM,...

In a landmark paper, George and Hwang (2004) show that a stock's 52-week high price largely explains the momentum effect and that a strategy based on closeness to the 52-week high has better forecasting power for future returns than do momentum strategies. We find that the 52-week high strategy...

Stock prices are one of the most volatile economic variables and forecasting stock prices and their returns has proved very challenging, if not impossible. In this paper, we apply a battery of linear and nonlinear models to forecast the returns in nine international stock exchanges for the...

We investigate the stock market crashes in China, Iceland, and the US in the 2007-2009 period. The bond stock earnings yield difference model is used as a prediction tool. Historically, when the measure is too high, meaning that long bond interest rates are too high relative to the trailing...

This paper examines the time-series predictability of aggregate stock returns in 20 emerging markets. In contrast to the aggregate-level findings in US, earnings yield forecasts the time-series of aggregate stock returns in emerging markets. We consider aggregate earnings not as normalizing...

We investigate lead-lag relationships among country stock returns and identify a leading role for the United States: lagged U.S. returns significantly predict returns in numerous non-U.S. industrialized countries (after controlling for national economic variables and countries' own lagged...

This paper explores the implications of a dividend yield model for predicting aggregate Japanese stock returns using long time-series data from 1949 to 2009. In addition to one-period return tests, we conduct statistical tests based on dividend growth forecasts and long-horizon return forecasts...

This paper analyzes recursive and rolling neural network models to forecast one-step-ahead sign variations in gold price. Different combinations of techniques and sample sizes are studied for feed forward and ward neural networks. The results shows the rolling ward networks exceed the recursive...