The Role of Artificial Intelligence in Optimizing Portfolio Management: A Literature Review

Artificial Intelligence (AI) assumes an increasingly pivotal role in the domain of financial asset management, endowing it with sophisticated capabilities in data analysis, modeling, prediction, and automation, thereby significantly augmenting the intricacies of asset management processes. The efficacy of AI is particularly evident in the realm of asset allocation strategies, notably within the Black-Litterman model where it furnishes an array of tools conducive to an enhanced understanding of investor sentiment. In this paper, the authors analyze recent studies that have focused on the application of artificial intelligence in financial portfolio management. Our main contribution is to clarify the added value that artificial intelligence, particularly machine learning and deep learning, brings to optimizing portfolio management. This involves providing more accurate allocation strategies and predictions, all achieved with improved speed and efficiency. Emphasis is placed on the substantive contribution of artificial intelligence to the refinement of the Black-Litterman model, facilitating a more adept modeling of investor views through the application of diverse methodologies, such as technical analysis or text data analysis.