Stock picking with machine learning - Zhu, Bangyuan (Nanyang Technological University, 2024)
In recent years, deep learning models based on neural networks have revolutionized the field of artificial intelligence. Unlike traditional machine learning approaches, deep learning models extract intricate features from raw data and perform end-to-end predictions, minimizing manual intervention and information loss associated with multi-step learning processes. However, when applied to multi-feature stock selection tasks, existing deep learning models may encounter limitations, necessitating the design of customized network structures for optimal effectiveness.