Industry return predictability, timing and profitability

Abstract

This paper aims to investigate the predictability of Australian industrial stock returns. Several identified economic variables are found to contain significant predictive power over industry portfolio returns in a Bayesian dynamic forecasting model. The Bayesian updating process was also applied in an investigation of out-of-sample prediction, timing ability and the profitability of an investment strategy of industry-rotation. When the predictor variables are employed in out-of-sample analysis, the predictive power is superior to the naïve prediction. The timing ability and profitability associated with predictability are also economically significant. When the industry momentum is examined, the results show that a group-rotation strategy can enhance the portfolio performance.