Deep Learning Approaches for Stock Price Forecasting Post Covid19: A Survey

The post-covid era is marked by the massive use of new communication technologies, in particular the application of artificial intelligence in all aspects of daily life. The use of trading platforms and applications by individuals and professionals alike has prompted researchers to design new predictive model architectures based on deep learning, to integrate the maximum amount of information generated by the unprecedented use of social networks to handle the complex patterns of financial time series, in addition to traditional data based on technical and fundamental analysis. In this paper we will look at some of the most important developments in this field, regarding to the novel trend of implementation of neural network-based hybrid model, that takes the edge in domain of stock price prediction, those approaches comes to deal with numerical and non-numerical data to get improved performance in prediction field.