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Deep Learning for Decision Making and the Optimization of Socially Responsible Investments and Portfolio

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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.

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  • Nhi N.Y.Vo & Xue-Zhong He & Shaowu Liu & Guandong Xu, 2019. "Deep Learning for Decision Making and the Optimization of Socially Responsible Investments and Portfolio," Published Paper Series 2019-3, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    • Handle: RePEc:uts:ppaper:2019-3
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    Keywords

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