Before revision:  Recurrent Neural Networks (RNNs)  are applied to stock return predictions. We build portfolios by adjusting potential return threshold levels used to classify assets, and obtain  risk-return profiles examining their statistical properties.
After revision:  Recurrent Neural Networks (RNNs) are applied to the investment universe consisted of ten stocks in the S risk-return profiles examining their statistical properties.