Indicator selection and stock return predictability

We propose a momentum-determined indicator-switching (MDIS) strategy, simple and effective, to improve the predictability of stock returns, which can effectively select predictors. Empirical results indicate that the stock return forecasts generated by the MDIS strategy are statistically and economically significant. And we find that super long-term momentum of predictability (SMoP) exists in predictive factors. That is, in a long period of time in the past, the best predictor among a series of factors has best prediction ability in the future. We also design restricted momentum-determined indicator-switching (RMDIS) strategy when considering economic constrain. It is robust for the prediction performance of this strategy using a series of extension and robustness test. Success of the RMDIS strategy is also seen in using technical indicators to forecast stock returns.

Automated summary

The study introduces a momentum-determined indicator-switching (MDIS) strategy to improve the predictability of stock returns by effectively selecting predictors. Empirical results show significant impact of the MDIS strategy on stock return forecasts, revealing the existence of super long-term momentum of predictability. A restricted version of the strategy (RMDIS) is also designed to consider economic constraints, showing robust prediction performance through various tests. The success of the RMDIS strategy is evident in using technical indicators to forecast stock returns.