基于深度强化学习的股市投资模型构建及实证研究
发布时间：2018-09-17 06:27
【摘要】：股票市场在整个金融市场中起到很重要的作用,如何在股市中获取有效的交易信号是股市投资一直在探讨的话题。本文首先综述了深度强化学习理论及模型,进而以深度学习和强化学习为基础,结合深度强化学习相关理论模型,从自动化股市投资交易决策机制构建角度构造股市深度强化学习模型。在股市投资策略中使用深度强化学习模型进行策略的构建是有效的,从各项策略评估指标结果显示深度强化学习模型对KD指标交易信号抓取的有效性要比单纯的KD指标交易要有效,通过深度强化学习构建的交易模型可以应用到投资策略的构建中。同时对个股的评估中发现深度强化学习策略是大概率获利策略,需要分散投资来减少投资风险,实现大概率获利。本文构建了以深度强化学习为理论基础的股市投资策略模型,并通过实证数据验证了该模型的有效性,揭示了深度强化学习在股市投资策略构建的内在逻辑。这对投资者自动化投资模型构建、股市投资策略的构建、人工智能在金融投资领域的应用和提高投资者策略收益率都做出了有益的借鉴。
[Abstract]:Stock market plays an important role in the whole financial market. How to obtain effective trading signals in stock market is a topic that stock market investment has been discussing all the time. This paper first summarizes the theory and model of deep reinforcement learning, and then combines the related theory model of depth reinforcement learning with depth learning and reinforcement learning as the foundation. From the perspective of automatic stock market investment and trading decision-making mechanism, the paper constructs a stock market depth reinforcement learning model. It is effective to use the deep reinforcement learning model to construct the strategy in the stock market investment strategy. The results of each strategy evaluation index show that the depth reinforcement learning model is more effective than the pure KD index in grasping the trading signal of KD index. The transaction model constructed by deep reinforcement learning can be applied to the construction of investment strategy. At the same time, it is found in the evaluation of individual stocks that the deep reinforcement learning strategy is a high-probability profit-making strategy, which requires diversification to reduce the investment risk and realize the high-probability profit-making. In this paper, a stock market investment strategy model based on deep reinforcement learning is constructed, and the validity of the model is verified by empirical data, which reveals the inherent logic of deep reinforcement learning in the construction of stock market investment strategy. It can be used for reference for the construction of investor's automatic investment model, the construction of stock market investment strategy, the application of artificial intelligence in the field of financial investment and the improvement of the return rate of investor strategy.
【学位授予单位】：广东财经大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F832.51
本文编号：2244990
[Abstract]:Stock market plays an important role in the whole financial market. How to obtain effective trading signals in stock market is a topic that stock market investment has been discussing all the time. This paper first summarizes the theory and model of deep reinforcement learning, and then combines the related theory model of depth reinforcement learning with depth learning and reinforcement learning as the foundation. From the perspective of automatic stock market investment and trading decision-making mechanism, the paper constructs a stock market depth reinforcement learning model. It is effective to use the deep reinforcement learning model to construct the strategy in the stock market investment strategy. The results of each strategy evaluation index show that the depth reinforcement learning model is more effective than the pure KD index in grasping the trading signal of KD index. The transaction model constructed by deep reinforcement learning can be applied to the construction of investment strategy. At the same time, it is found in the evaluation of individual stocks that the deep reinforcement learning strategy is a high-probability profit-making strategy, which requires diversification to reduce the investment risk and realize the high-probability profit-making. In this paper, a stock market investment strategy model based on deep reinforcement learning is constructed, and the validity of the model is verified by empirical data, which reveals the inherent logic of deep reinforcement learning in the construction of stock market investment strategy. It can be used for reference for the construction of investor's automatic investment model, the construction of stock market investment strategy, the application of artificial intelligence in the field of financial investment and the improvement of the return rate of investor strategy.
【学位授予单位】：广东财经大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F832.51
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