Interpretable Deep Learning for Stock Returns: A Consensus-Bottleneck Asset Pricing Model

This article introduces a research paper on using interpretable deep learning for stock return prediction. The focus is on developing a model that not only predicts stock returns but also provides insights into the factors driving those predictions. The 'Consensus-Bottleneck Asset Pricing Model' suggests a novel approach to asset pricing.

• •Focuses on interpretable deep learning for stock return prediction.
• •Proposes a 'Consensus-Bottleneck Asset Pricing Model'.
• •Aims to provide insights into the factors driving stock return predictions.