Intelligent Asset Allocation using Predictions of Deep Frequency Decomposition

作者：

Highlights：

• This paper introduces a deep Frequency decomposition model as a stock prediction model.

• The role of introduced prediction model in the portfolio management is highlighted.

• The Black-Litterman model is addressed as a proper response to the investors’ subjective views.

• The collaboration of the models above could make the intelligent asset allocation more effective.

摘要

•This paper introduces a deep Frequency decomposition model as a stock prediction model.•The role of introduced prediction model in the portfolio management is highlighted.•The Black-Litterman model is addressed as a proper response to the investors’ subjective views.•The collaboration of the models above could make the intelligent asset allocation more effective.

论文关键词：Asset allocation,Black-litterman,LSTM,CNN,CEEMD

论文评审过程：Received 31 December 2020, Revised 13 July 2021, Accepted 2 August 2021, Available online 11 August 2021, Version of Record 14 August 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115715