【摘要】：股票市場在整個金融市場中起到很重要的作用,如何在股市中獲取有效的交易信號是股市投資一直在探討的話題。本文首先綜述了深度強化學習理論及模型,進而以深度學習和強化學習為基礎,結合深度強化學習相關理論模型,從自動化股市投資交易決策機制構建角度構造股市深度強化學習模型。在股市投資策略中使用深度強化學習模型進行策略的構建是有效的,從各項策略評估指標結果顯示深度強化學習模型對KD指標交易信號抓取的有效性要比單純的KD指標交易要有效,通過深度強化學習構建的交易模型可以應用到投資策略的構建中。同時對個股的評估中發(fā)現(xiàn)深度強化學習策略是大概率獲利策略,需要分散投資來減少投資風險,實現(xiàn)大概率獲利。本文構建了以深度強化學習為理論基礎的股市投資策略模型,并通過實證數(shù)據(jù)驗證了該模型的有效性,揭示了深度強化學習在股市投資策略構建的內(nèi)在邏輯。這對投資者自動化投資模型構建、股市投資策略的構建、人工智能在金融投資領域的應用和提高投資者策略收益率都做出了有益的借鑒。
[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.
【學位授予單位】：廣東財經(jīng)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F832.51

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