Stock Return Prediction

Stock return prediction aims to forecast future stock market performance, a crucial task for investment decisions and portfolio optimization. Current research emphasizes developing sophisticated models that capture complex market dynamics, including the use of deep learning architectures like Long Short-Term Memory networks (LSTMs), Graph Neural Networks (GNNs), and transformer-based models, often incorporating alternative behavioral economic frameworks and integrating diverse data sources such as news sentiment, economic indicators, and social media activity. These advancements aim to improve prediction accuracy and robustness, ultimately leading to more efficient portfolio management and potentially more informed investment strategies.