检测主要股票市场的崩溃和反弹
Detection of Crashes and Rebounds in Major Equity Markets
摘要：
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，许多研究的目的是了解、识别和预测金融市场的崩溃和反弹。Johansen-Ledoit-Sornette（JLS）模型提供了一个操作框架来理解和诊断合理预期的金融泡沫，最近被扩展到负泡沫和反弹。使用JLS模型，我们开发了一个报警指数的基础上，先进的模式识别方法，其目的是检测泡沫和执行预测的市场崩溃和反弹。在全球10个主要股市上测试我们的方法，我们定量地表明，我们开发的警报在预测市场崩溃和反弹方面的表现要比机会好得多。我们使用衍生信号来开发基本的交易策略，这些策略在统计上比简单的买入并持有策略产生更好的表现。
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
