摘要翻译：
我们引入“负泡沫”的概念作为标准金融泡沫的镜像，其中正反馈机制可能导致短暂的加速价格下跌。为了模拟这些负泡沫，我们采用了理性预期泡沫的Johansen-Ledoit-Sornette(JLS)模型，用一个描述噪声交易者集体购买压力的危险率来描述。在短暂的负泡沫期间发生的价格下跌可以被解释为一种有效的随机首付，理性代理人接受支付，希望从可能的反弹的预期发生中获利。我们验证了该模型，表明它在识别主要市场反弹的时间方面具有显著的预测能力。这一结果是通过使用一种通用的模式识别方法得到的，该方法结合了从JLS模型的动态校准中多次获得的信息。误差图、贝叶斯推理和交易策略表明，用JLS模型校准负泡沫可以提取真实信息，获得真正的技巧。我们得出结论，负泡沫通常与大反弹或大反弹相关，这是标准泡沫终结的崩溃的镜像。
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英文标题：
《Diagnosis and Prediction of Market Rebounds in Financial Markets》
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作者：
Wanfeng Yan and Ryan Woodard and Didier Sornette
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最新提交年份：
2011
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：General Finance        一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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英文摘要：
  We introduce the concept of "negative bubbles" as the mirror image of standard financial bubbles, in which positive feedback mechanisms may lead to transient accelerating price falls. To model these negative bubbles, we adapt the Johansen-Ledoit-Sornette (JLS) model of rational expectation bubbles with a hazard rate describing the collective buying pressure of noise traders. The price fall occurring during a transient negative bubble can be interpreted as an effective random downpayment that rational agents accept to pay in the hope of profiting from the expected occurrence of a possible rally. We validate the model by showing that it has significant predictive power in identifying the times of major market rebounds. This result is obtained by using a general pattern recognition method which combines the information obtained at multiple times from a dynamical calibration of the JLS model. Error diagrams, Bayesian inference and trading strategies suggest that one can extract genuine information and obtain real skill from the calibration of negative bubbles with the JLS model. We conclude that negative bubbles are in general predictably associated with large rebounds or rallies, which are the mirror images of the crashes terminating standard bubbles.
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PDF链接：
https://arxiv.org/pdf/1003.5926