Deep learning for decision making and the optimization of socially responsible investments and portfolio

Nhi N.Y. Vo, Xuezhong He, Shaowu Liu, Guandong Xu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

84 Citations (Scopus)

Abstract

A socially responsible investment portfolio takes into consideration the environmental, social and governance aspects of companies. It has become an emerging topic for both financial investors and researchers recently. Traditional investment and portfolio theories, which are used for the optimization of financial investment portfolios, are inadequate for decision-making and the construction of an optimized socially responsible investment portfolio. In response to this problem, we introduced a Deep Responsible Investment Portfolio (DRIP) model that contains a Multivariate Bidirectional Long Short-Term Memory neural network, to predict stock returns for the construction of a socially responsible investment portfolio. The deep reinforcement learning technique was adapted to retrain neural networks and rebalance the portfolio periodically. Our empirical data revealed that the DRIP framework could achieve competitive financial performance and better social impact compared to traditional portfolio models, sustainable indexes and funds.

Original languageEnglish
Article number113097
JournalDecision Support Systems
Volume124
DOIs
Publication statusPublished - Sept 2019
Externally publishedYes

Keywords

  • Decision support systems
  • Deep reinforcement learning
  • Multivariate analytics
  • Portfolio optimization
  • Socially responsible investment

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