A statistical model of speculative bubbles, with applications to the stock markets of the United States, Japan, and China
A statistical model of speculative bubbles, with applications to the stock markets of the United States, Japan, and China
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DOI：
10.1016/j.jbankfin.2013.02.015
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发表时间：
2013-07
影响因子：
3.7
通讯作者：
Kazumi Asako;Zhentao Liu
中科院分区：
文献类型：
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作者：
Kazumi Asako;Zhentao Liu
众所周知，价格越是偏离基本面，价格逆转的可能性就越大。考虑到这一点，我们提出了一个简单的统计模型来识别金融市场中的投机泡沫。通过对包括转变概率在内的时变参数的估计，我们可以确定新生的气泡何时以及如何随着时间的推移而增长和破裂。该模型可以通过递归计算来估计，这需要标准计算机的巨大存储容量。为此，我们在计算中引入了一个近似值，保持了我们估计技术的递归性质。然后我们将该模型应用于美国、日本和中国的股票市场，估计了其参数和泡沫破裂的概率，得到了几个有趣的结果：股价泡沫的时间序列数据显示出内在的非平稳发展，并且泡沫破裂的概率确实随着股价的过高或过低而增加。
It is common knowledge that the more prices deviate from fundamentals, the more likely it is for prices to reverse. Taking this into account, we propose a simple statistical model to identify speculative bubbles in financial markets. Through the estimates of the time varying parameters, including transition probabilities, we can identify when and how newly born bubbles grow and burst over time. The model can be estimated by recursive computations, which require a huge storage capacity for standard computers. For this reason, we introduce an approximation in the computation, maintaining the recursive nature of our estimation technique. We then apply this model to the stock markets of the United States, Japan, and China, estimate its parameters and the probabilities of a bubble crash, and obtain several interesting results: the time series data of the stock price bubble show an inherently non-stationary development and the probability of a bubble crash indeed increases as the stock price becomes too high or too low.