股市泡沫周期演化机制与复杂性特征研究——以上海证券交易市场为例

The Cyclical Evolutionary Mechanism and Complexity Characteristics of Stock Market Bubbles——Take Shanghai Stock Exchange as a Case

股票市场泡沫是一种非常重要的资产价格泡沫类型。由于股票市场本身是一个典型的非线性系统,从而隐含于股票价格波动之中的泡沫成分的演化行为也具有了复杂性系统的典型特征。深入研究股市泡沫的周期演化机制与复杂性特征,对于科学发现股票市场价格泡沫的运行规律具有非常重要的理论和现实意义。文章基于宏观因素构建的股票市场泡沫测度模型,以上海证券交易市场为对象,研究1991-2014年间我国股票市场泡沫的周期演化机制,在此基础上,应用分形理论中的R/S方法研究我国股票市场泡沫周期演化过程中所隐含的复杂性特征。研究结果显示:我国股票市场泡沫存在自增强式的周期性演化机制,演化过程具有长记忆性、正反馈效应、波动集聚性和轨道周期性等复杂非线性系统特征。文章的研究对于科学发现我国股票市场泡沫演化内在规律,进而建立有效的金融市场监管与政策体系具有重要启示。

The stock market bubble is one of the most important types of asset price bubbles. As the stock market is a typical nonlinear system, the evolutionary behavior of bubbles components, implied in the stock price fluctuation, has the typical characteristics of complexity system. To develop a thorough research on the cyclical evolutionary mechanism and complexity characteristics of stock market bubbles, it is of great significance and theory to discover the operational law for stock market bubbles scientifically. Taking Shanghai Stock Exchange as a case, the model, based on macroeconomic factors to measure the stock market bubbles, investigates the cyclical evolutionary mechanism of Chinese stock market bubbles for the periods between 1991-2014. The R/S method of the fractal theory is applied to analyze the complexity characteristics, which are implied in the evolutionary process for Chinese stock market bubbles. The conclusions show that a self-reinforced cyclical evolutionary mechanism consists in the bubbles＇ process, and there are many charac-teristics of the complex nonlinear system as long memory, positive feedback effect, volatility clustering, and periodic orbit. The conclusions provides an important enlightenment to a thorough understanding of the inherent law for evolutionary process of Chinese stock market bubbles, as well as the establishment of an effective regulation and policy system for financial market of China.