规划识别在股市趋势分析的应用研究

发布时间：2018-03-30 04:19

本文选题：股市趋势　切入点：规划识别　出处：《江苏科技大学》2012年硕士论文

【摘要】：自从股票市场诞生以来，人们就想利用股票市场中提供的各个信号去分析和预测未来的股票的走势，由此来获取利益。从最早非理性的“裙摆理论”的预测到运用科学理论的统计学和图形学的“基本面分析”和“技术性分析”等方法，这些理论在不同的时期都取得了一定的效果。在新时期，随着计算机技术的发展，计算机技术被广泛应用到各个领域，并且取得了不错的效果。所以人们希望将这个新的技术运用到股市分析当中，能够帮助我们在股市当中获取利益和规避风险。针对于此，许多学者做出了大量的研究工作，如：将神经网络、数据挖掘等人工智能方法运用到股市预测当中，并且取得了一定的效果。但是，这些方法大多是从历史数据中，根据历史经验来推测出未来价格的变动，但是股市当中存在着大量的欺骗和博弈，往往单纯的根据历史数据很难得到合理的推论结果。本文是将规划识别的方法运用到股市当中，规划识别问题是属于心理学和人工智能的一个交叉学科,它涉及到知识表达、知识推理、非单调逻辑、情景演算、人工交互、知识挖掘等多方面知识。规划识别中有很多方法，其中规划识别中的基于抽象策略的规划识别是很适合股市推测的方法，，该方法主要运用在有噪声和不确定领域的识别方法。它可以建立了多层推理，在概率推理层应用马尔科夫链模型作为概率推理。然后由于股市投资的每种不用的投资动作都会产生不同的效用，因此在第二层中引入效用函数，运用决策理论方法，来获取较为更为合理的决策。最后可利用策略迭代层来降低计算复杂度。本文最后通过实例对策略规划方法的有效性进行了验证，并取得了较好的效果，通过对本文的总结和分析，对规划识别在股市分析的前景进行展望。
[Abstract]:Since the birth of the stock market, people have wanted to use the signals provided in the stock market to analyze and predict the future trend of stocks. From the prediction of the earliest irrational "skirt theory" to the "fundamental analysis" and "technical analysis" of statistics and graphics using scientific theory, These theories have achieved certain results in different periods. In the new era, with the development of computer technology, computer technology has been widely used in various fields. So people hope that applying this new technology to stock market analysis can help us gain profits and avoid risks in the stock market. In view of this, many scholars have done a lot of research work, such as: neural network, data mining and other artificial intelligence methods used in stock market forecasting, and achieved certain results. Most of these methods are based on historical data, according to historical experience to extrapolate future price changes, but there are a lot of deception and game in the stock market, it is often difficult to get reasonable corollary results simply based on historical data. This paper applies the method of planning recognition to the stock market. The problem of planning recognition is an interdisciplinary subject of psychology and artificial intelligence. It involves knowledge expression, knowledge reasoning, non-monotone logic, scenario calculus, artificial interaction. There are many methods in planning recognition, in which abstract strategy based planning recognition is very suitable for stock market speculation. This method is mainly used in the identification of noisy and uncertain fields. The Markov chain model is used as probabilistic reasoning in the probabilistic reasoning layer. Then, because every kind of investment action of stock market investment will produce different utility, the utility function is introduced in the second layer, and the decision theory method is used. Finally, the strategy iteration layer can be used to reduce the computational complexity. Finally, the effectiveness of the policy planning method is verified by an example, and good results are obtained. Through the summary and analysis of this paper, the prospect of planning identification in stock market analysis is prospected.
【学位授予单位】：江苏科技大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：F224;F832.51

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