2021
Augmenting Transferred Representations for Stock Classification
ICASSP 2021accepted
Stock classification is a challenging task due to high levels of noise and volatility of stocks returns. In this paper we show that using transfer learning can help with this task, by pre-training a model to extract universal features on the full universe of stocks of the S&P500 index and then trans…