本文研究股票市场混沌时间序列的长期演化规律。本文借助最大信息熵原理推导了弱时间关联性时间序列波动强度的定态概率分布 ;在介绍了时间序列联合概率和条件概率含义的基础上 ,借助最大定标原理 ,讨论了具有弱时间关联性的股票市场长期行为的联合概率分布与条件概率分布 ;研究了两类再生概率分布 ,并给出四种系统风险度量评价指标。最后 ,本文对中国沪市股票市场进行了实证研究 This article studies the long-term evolution of the chaotic time series in the stock market. In this paper, the maximum probability of information entropy is used to derive the steady-state probability distribution of the intensity of weak time-related time series fluctuations. Based on the introduction of the joint probabilities of time series and conditional probabilities, with the help of the principle of maximum scaling, The joint probability distribution and conditional probability distribution of long-term behavior in stock market are studied. Two types of probability distribution of regeneration are studied and four kinds of evaluation indexes of systematic risk measurement are given. Finally, this paper conducts empirical research on the stock market of Shanghai Stock Exchange in China