摘要翻译：
众所周知，金融市场以其影响世界大部分人口的戏剧性动态和后果而闻名。因此，许多研究旨在理解、识别和预测金融市场的崩溃和反弹。Johansen-Ledoit-Sornette(JLS)模型提供了一个从理性预期理解和诊断金融泡沫的操作框架，最近被扩展到负泡沫和负反弹。利用JLS模型，我们开发了一个基于先进模式识别方法的预警指标，目的是检测泡沫，并对市场崩溃和反弹进行预测。我们在全球10个主要股票市场上测试了我们的方法，从数量上表明，我们开发的警报在预测市场崩溃和反弹方面比chance表现得更好。我们使用导出的信号来开发基本的交易策略，这些策略比简单的买入和持有策略产生更好的统计性能。
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英文标题：
《Detection of Crashes and Rebounds in Major Equity Markets》
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作者：
Wanfeng Yan, Reda Rebib, Ryan Woodard, 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：
  Financial markets are well known for their dramatic dynamics and consequences that affect much of the world's population. Consequently, much research has aimed at understanding, identifying and forecasting crashes and rebounds in financial markets. The Johansen-Ledoit-Sornette (JLS) model provides an operational framework to understand and diagnose financial bubbles from rational expectations and was recently extended to negative bubbles and rebounds. Using the JLS model, we develop an alarm index based on an advanced pattern recognition method with the aim of detecting bubbles and performing forecasts of market crashes and rebounds. Testing our methodology on 10 major global equity markets, we show quantitatively that our developed alarm performs much better than chance in forecasting market crashes and rebounds. We use the derived signal to develop elementary trading strategies that produce statistically better performances than a simple buy and hold strategy.
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PDF链接：
https://arxiv.org/pdf/1108.0077