[2T1-GS-10] AI application

[2T1-GS-10-01] Proposed asset allocation based on sentiment signals considering causal relationships

〇Rei Taguchi¹, Hiroki Sakaji¹, Kiyoshi Izumi¹ (1. The University of Tokyo)

[[Online]]

Keywords:financial news, MLM scoring, causal inference, change-point detection, portfolio optimization

This study demonstrates whether the financial text is useful for using stocks in the tactical asset allocation method. This can be achieved using natural language processing to create polarity indexes in financial news. We perform clustering of the created polarity indexes using the change point detection algorithm. In addition, we construct a stock portfolio and rebalanced it at each change point using an optimization algorithm. Consequently, the proposed asset allocation method outperforms the comparative approach. This result suggests that the polarity index is useful for constructing the equity asset allocation method.