Constructing Sentiment Signal-Based Asset Allocation Method with Causality Information

Author:

Taguchi ReiORCID,Sakaji Hiroki,Izumi Kiyoshi,Murayama Yuri

Abstract

AbstractThis study demonstrates whether financial text is useful for the tactical asset allocation method using stocks. 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.

Funder

JST-Mirai Program

The University of Tokyo

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Theoretical Computer Science,Software

Reference59 articles.

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