中国股市建模与市场生态研究

发布时间：2018-01-19 11:20

本文关键词： 金融物理基于Agent的计算经济学市场生态典型特征　出处：《南京信息工程大学》2013年硕士论文　论文类型：学位论文

【摘要】：近年来学者们在对金融市场进行实证分析时发现,金融价格时间序列具有尖峰胖尾、尾部负三次方定律和长程相关性等典型统计特征,且这些实证结果明显与传统的有效市场假说相悖。面对这一经济学窘境,本文以构建基于Agent的计算经济学模型为基础,研究金融市场价格波动统计特征的内在形成机理,并通过研究投资者的组成、相互作用和活动程度与价格波动的关系尝试给出价格波动的生态学解释。本文主要做了以下四方面工作： (一)从描述Agent异质性和适应性的角度出发,引入了价格敏感度和交易反馈时间这两个参数,建立一个拥有基本面投资者、动量交易者、反转交易者和噪声交易者,且符合中国股票市场交易规则的基于Agent的计算经济学模型。 (二)通过分析模型产生的价格时间序列,发现模型能够再现真实市场的尖峰胖尾特性、中心部分满足列维分布、尾部满足负三次方定律和波动长程相关的典型统计特征,并且特征值与真实市场较为吻合。 (三)调整模型参数,研究各个参数对统计特征值的影响时发现：若股息维持不变的时间越长,短时间尺度上小价格波动发生的概率就越大；动量交易者的剧烈活动造成了短时间尺度上大价格波动的产生；基本面投资者在市场中扮演着抑制大价格波动的角色；随着动量交易者和反转交易者更积极地参与市场交易,短时间尺度上的小价格波动就会增多。 (四)从不同类型投资者之间相互作用的角度,对模型中Agent的活动比率数据作统计分析,并给出价格波动的生态学解释：动量和反转交易者参与市场的比例会随着基本面交易者的活跃而增加,并且动量和反转交易者彼此促进对方的活跃程度；随着Agent活动比率的增长,市场波动也随之加剧；基本面交易者不是大价格波动的制造者,而动量交易者和反转交易者促进了小价格波动的产生；平均市场期望与收益以及投资者活动比率负相关；基本面投资者的活动比率与收益之间,以及平均市场期望与投资者活动比率之间存在着幂律关系。
[Abstract]:In recent years, in the empirical analysis of financial markets, scholars found that financial price time series has the typical statistical characteristics, such as peak, fat tail, tail negative third power law and long range correlation. These empirical results are obviously contrary to the traditional efficient market hypothesis. In the face of this economic dilemma, this paper builds a computational economics model based on Agent. This paper studies the intrinsic formation mechanism of the statistical characteristics of price volatility in financial markets, and studies the composition of investors. This paper tries to give an ecological explanation of price volatility. (1) from the angle of describing the heterogeneity and adaptability of Agent, this paper introduces two parameters, price sensitivity and trading feedback time, to establish a momentum trader with fundamental investors. Inversion traders and noise traders, and the computational economics model based on Agent, which conforms to the trading rules of Chinese stock market. (2) by analyzing the price time series produced by the model, it is found that the model can reproduce the peak and fat tail characteristics of the real market, and the center part satisfies the Levi distribution. The tail satisfies the typical statistical characteristics of the negative cubic law and the long-range correlation of fluctuations, and the eigenvalues are in good agreement with the real market. (3) adjusting the model parameters and studying the influence of each parameter on the statistical eigenvalue, it is found that the longer the dividend remains constant, the greater the probability of small price fluctuation will occur on a short time scale; The intense activity of momentum traders results in large price fluctuations on a short time scale. Fundamental investors play a role in restraining large price fluctuations in the market; As momentum traders and reverse traders participate more actively in the market, small price volatility increases in a short period of time. (4) from the point of view of the interaction between different types of investors, the activity ratio data of Agent in the model are statistically analyzed. The ecological explanation of price fluctuation is given: momentum and the proportion of reverse traders participating in the market will increase with the activity of fundamental traders, and momentum and reverse traders promote each other's activity; With the increase of Agent activity ratio, market volatility also intensifies. Fundamental traders are not the producers of large price fluctuations, while momentum traders and reverse traders promote the production of small price fluctuations. The average market expectation is negatively correlated with the return and the ratio of investor activity; There is a power law relationship between the activity ratio of the fundamental investors and the return, and between the average market expectation and the investor activity ratio.
【学位授予单位】：南京信息工程大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP18;F832.51

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