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摘要翻译：
最近在[1]中讨论了市场恐慌的横截面特征在日时间尺度上，在这里扩展到研究股票在日内时间尺度上的横截面特征。我们确认了离散度和峰度的特定日内模式，并发现在恐慌时期，股票之间的相关性增加，收益率符号之和呈双峰分布。我们还发现相关中存在记忆，以指数0.05的幂律衰减。在2010年5月6日的闪电崩盘期间，我们发现离散度急剧增加，相关性增加。然而，峰度仅略有下降，相比之下，在日常时间尺度上，峰度在恐慌时急剧下降。我们的研究表明，这种行为差异是引起恐慌的波动性冲击的起源的结果：波动性冲击的跨股相关性越大，峰度越小；冲击越特殊，这种效应越小，峰度与离散度呈正相关。我们还发现，相关性存在杠杆效应：负收益往往先于相关性的增加。一个带有倾斜的股票价格反馈模型与一个跟随市场波动的相关动力学相结合，很好地解释了我们的观察。
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英文标题：
《Market panic on different time-scales》
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作者：
Lisa Borland and Yoan Hassid
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最新提交年份：
2010
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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：
Cross-sectional signatures of market panic were recently discussed on daily time scales in [1], extended here to a study of cross-sectional properties of stocks on intra-day time scales. We confirm specific intra-day patterns of dispersion and kurtosis, and find that the correlation across stocks increases in times of panic yielding a bimodal distribution for the sum of signs of returns. We also find that there is memory in correlations, decaying as a power law with exponent 0.05. During the Flash-Crash of May 6 2010, we find a drastic increase in dispersion in conjunction with increased correlations. However, the kurtosis decreases only slightly in contrast to findings on daily time-scales where kurtosis drops drastically in times of panic. Our study indicates that this difference in behavior is result of the origin of the panic-inducing volatility shock: the more correlated across stocks the shock is, the more the kurtosis will decrease; the more idiosyncratic the shock, the lesser this effect and kurtosis is positively correlated with dispersion. We also find that there is a leverage effect for correlations: negative returns tend to precede an increase in correlations. A stock price feed-back model with skew in conjunction with a correlation dynamics that follows market volatility explains our observations nicely.
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PDF链接：
https://arxiv.org/pdf/1010.4917
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