摘要翻译：
对数周期幂律模型结合了理性预期泡沫的经济理论、投资者和交易者模仿和羊群行为金融学以及分叉和相变的数学和统计物理，成为一种灵活的泡沫检测工具。LPPL模型将加速振荡修饰的资产价格的快于指数的（具有有限时间奇异性的幂律）增长作为泡沫的主要诊断。它体现了一个高回报预期的正反馈循环，与崩盘预期的负反馈螺旋相竞争。本文利用LPPL模型对2005年5月至2009年7月中国股票市场两个重要指数的两次泡沫和随后的市场崩溃进行了实证分析。上证综合指数和深证成分股指数在两个不同的时间段都表现出这种行为：1）从2005年年中开始，在2007年10月爆发；2）从2008年11月开始，在2009年8月初爆发。我们成功地提前预测了这两次崩盘的时间窗口，方法与成功预测2006年年中美国房地产泡沫的峰值和2008年7月全球石油泡沫的峰值所用的方法相同。最近中国指数中的泡沫被检测到，它的结束或变化由两组独立预测，结果相似，表明模型已经被充分证明，可以被工业从业者复制。在这里，我们提出了更详细的分析个别中国指数预测和方法，用于作出和检验他们。
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英文标题：
《Bubble Diagnosis and Prediction of the 2005-2007 and 2008-2009 Chinese
  stock market bubbles》
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作者：
Zhi-Qiang Jiang, Wei-Xing Zhou, Didier Sornette, Ryan Woodard, Ken
  Bastiaensen, Peter Cauwels
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最新提交年份：
2009
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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英文摘要：
  By combining (i) the economic theory of rational expectation bubbles, (ii) behavioral finance on imitation and herding of investors and traders and (iii) the mathematical and statistical physics of bifurcations and phase transitions, the log-periodic power law model has been developed as a flexible tool to detect bubbles. The LPPL model considers the faster-than-exponential (power law with finite-time singularity) increase in asset prices decorated by accelerating oscillations as the main diagnostic of bubbles. It embodies a positive feedback loop of higher return anticipations competing with negative feedback spirals of crash expectations. We use the LPPL model in one of its incarnations to analyze two bubbles and subsequent market crashes in two important indexes in the Chinese stock markets between May 2005 and July 2009. Both the Shanghai Stock Exchange Composite and Shenzhen Stock Exchange Component indexes exhibited such behavior in two distinct time periods: 1) from mid-2005, bursting in Oct. 2007 and 2) from Nov. 2008, bursting in the beginning of Aug. 2009. We successfully predicted time windows for both crashes in advance with the same methods used to successfully predict the peak in mid-2006 of the US housing bubble and the peak in July 2008 of the global oil bubble. The more recent bubble in the Chinese indexes was detected and its end or change of regime was predicted independently by two groups with similar results, showing that the model has been well-documented and can be replicated by industrial practitioners. Here we present more detailed analysis of the individual Chinese index predictions and of the methods used to make and test them.
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PDF链接：
https://arxiv.org/pdf/0909.1007