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基于最优控制算法的蓝筹股投资策略研究

发布时间:2018-02-25 04:27

  本文关键词: 蓝筹股 灰色系统理论 最优控制算法 决策 出处:《陕西科技大学》2014年硕士论文 论文类型:学位论文


【摘要】:我国的股票市场从诞生至今,已经在风风雨雨中走过了20多年。如今,股票市场已经成为中国市场经济不可或缺的重要组成部分,且在整体经济份额中所占比例大。中国股市在经过20多年持续不断的逐步发展后,现已成为全球第二大市值市场。进入21世纪,股市在发展中走向成熟,国家在政策层面会减少对市场的干预和调节,这让经济市场在自由而正常发展的同时,股票投资者在进行股票投资时有了更多的选择,,但同时也增加了投资者在面对众多选择时做出决策的困难。 对于蓝筹股来说,所涉资金巨大,投资人数众多,大盘蓝筹股的走势会直接影响大盘走势,同时,股票投资者在某一板块内选择股票进行投资时,会给予该板块内的蓝筹股更多关注,因而对于蓝筹股的研究是重中之重。 本文的主要研究工作如下: (1)从股票的基础知识出发,对股价的影响因素进行阐述,分析上市公司的主要财务数据指标,为股票的灰色关联评价选取财务数据指标和股票的最优控制算法分析奠定理论基础。 (2)立足灰色系统理论,从上市公司所公布的财务报表中选择具有共识的数据指标,应用多目标灰色关联决策原理对选择出的具有代表性的蓝筹个股进行分析,计算出每一只个股的综合评价值,以实现对个股的评价和排序,比较个股的优劣,并将评价结果与所选股票的实际情况进行对比,以给投资者在选择股票时一定的决策支持。在选择财务数据指标时,由于存在选择偏好上的差异性,因而对于相同股票的综合评价结果也不尽相同。同时,由于时间段的选择不同,所选股票的实际涨跌幅度排序与综合评价结果排序的吻合度也可能不同。 (3)运用股票的价格模型和最优控制算法原理,对股价建立数学模型,在对股价模型进行求解过程中,通过对目标函数的确立,引入哈密顿函数,结合变分法和最小值原理,求出了最优控制的数学表达式。并对股价的波动序列进行检验和分析,用最优控制算法分析处理股价模型。针对股价波动序列的随机性和不确定性等特点,提出了比较理想的增量序列与实际涨跌序列去认识和评判股票的方法,并在评判结果差异较大时给出了该差异的合理解释。 (4)最后,以华夏幸福为例进行了实证验证,实证结果表明:通过最优控制算法求解出的股价增长序列与实际股价波动序列存在一定偏差,但总体来说,股价增长序列与实际股价波动序列两者的吻合度还是较高,是比较理想的,这说明本文给出的以控制算法求解股价波动序列理想值的方法具有一定的实用性和有效性。
[Abstract]:The stock market in China has been through the ups and downs for more than 20 years since it was born. Today, the stock market has become an indispensable and important part of China's market economy. After more than 20 years of continuous and progressive development, the Chinese stock market has now become the second largest market value market in the world. In 21th century, the stock market has matured in the process of development. At the policy level, the state will reduce its intervention and regulation of the market, which will allow the economic market to develop freely and normally, at the same time, stock investors will have more choices when they invest in stocks. But it also makes it harder for investors to make decisions in the face of many choices. For blue-chip stocks, the amount of money involved is huge and the number of people invested is large. The trend of large-cap blue chips will directly affect the trend of the larger market. At the same time, when stock investors choose stocks within a certain sector to invest, Will give more attention to blue-chip stocks in the plate, so blue-chip research is the top priority. The main work of this paper is as follows:. Based on the basic knowledge of stock, this paper expounds the influencing factors of stock price, and analyzes the main financial data indexes of listed companies. It lays a theoretical foundation for the selection of financial data index and the analysis of optimal control algorithm for stock grey correlation evaluation. Based on the grey system theory, selecting the common data index from the financial statements published by the listed company, and applying the multi-objective grey relational decision principle to analyze the representative blue-chip stocks selected. The comprehensive evaluation value of each stock is calculated to realize the evaluation and ranking of each stock, to compare the merits and demerits of each stock, and to compare the evaluation results with the actual situation of the selected stock. In order to give investors some decision support in selecting stock. When selecting financial data index, the comprehensive evaluation results for the same stock are different because of the difference of choice preference. Because of the different time periods, the order of the actual range of stock price and the order of the comprehensive evaluation results may be different. Using the stock price model and the principle of optimal control algorithm, the mathematical model of stock price is established. In the course of solving the stock price model, the Hamiltonian function is introduced through the establishment of the objective function, and the variational method and the principle of minimum value are combined. The mathematical expression of optimal control is obtained, and the stock price volatility series is tested and analyzed. The optimal control algorithm is used to analyze and process the stock price model. In this paper, an ideal incremental sequence and a real rise and fall series are proposed to recognize and judge the stock, and a reasonable explanation of the difference is given when the result of the judgment is quite different. Finally, taking Huaxia happiness as an example, the empirical results show that there is a deviation between the stock price growth sequence and the actual stock price fluctuation sequence, but generally speaking, The degree of agreement between the stock price growth series and the real stock price fluctuation series is still high, which shows that the method of solving the ideal value of the stock price volatility series by the control algorithm presented in this paper is practical and effective.
【学位授予单位】:陕西科技大学
【学位级别】:硕士
【学位授予年份】:2014
【分类号】:F832.51;O232

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