Anmerkungen:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments June 15, 2022 erstellt
Beschreibung:
This paper proposes a factor timing strategy with information from 146 characteristic-based factors and a deep learning approach to capture nonlinear predictability. The deep learning-based factor timing strategy generates the highest economic value compared with the unconditional and alternative linear machine learning-based portfolios and remains robust after controlling for traditional factor models and transaction costs. With the unique market structure of the Chinese stock market, we find that mispricing-based theory helps explain the factor timing via deep learning