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

机译:决策的深度学习以及对社会负责的投资和投资组合的优化

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摘要

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.
机译:具有社会责任感的投资组合考虑了公司的环境,社会和治理方面。最近,它已成为金融投资者和研究人员的新兴话题。用于优化金融投资组合的传统投资和组合理论不足以用于决策和构建对社会负责的优化投资组合。为解决此问题,我们引入了包含多变量双向长期短期记忆神经网络的深度责任投资组合(DRIP)模型,以预测用于构建对社会负责的投资组合的股票收益。深度强化学习技术适用于重新训练神经网络并定期重新平衡投资组合。我们的经验数据表明,与传统的投资组合模型,可持续指数和基金相比,DRIP框架可以实现具有竞争力的财务业绩和更好的社会影响。

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