预测金融极端事件：一个超指数增长的网络度测度
Forecasting Financial Extremes: A Network Degree Measure of Super-exponential Growth
摘要：
股票市场的投资者通常在牛市时贪婪，在熊市时恐惧。贪婪或恐惧迅速在投资者中蔓延。这就是所谓的羊群效应，通常会导致股票价格的快速波动。在这样的市场机制中，股票价格以超指数的速度变化，通常会出现趋势逆转，纠正之前的过度反应。本文通过对价格时间序列的价格网络化程度的度量，构建了一个衡量股票价格超指数增长幅度的指标。研究了12个主要的国际股票指数。误差图检验表明，这一新指标对金融极端情况具有很强的预测能力，无论是波峰还是波谷。通过改变用于构建误差图的参数，我们表明预测能力是非常强大的。新指标的性能优于LPPL模式识别指标。
英文摘要：
Investors in stock market are usually greedy during bull markets and scared during bear markets. The greed or fear spreads across investors quickly. This is known as the herding effect, and often leads to a fast movement of stock prices. During such market regimes, stock prices change at a super-exponential rate and are normally followed by a trend reversal that corrects the previous over reaction. In this paper, we construct an indicator to measure the magnitude of the super-exponential growth of stock prices, by measuring the degree of the price network, generated from the price time series. Twelve major international stock indices have been investigated. Error diagram tests show that this new indicator has strong predictive power for financial extremes, both peaks and troughs. By varying the parameters used to construct the error diagram, we show the predictive power is very robust. The new indicator has a better performance than the LPPL pattern recognition indicator.
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。
