英文标题：
《Zooming into market states》
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作者：
Desislava Chetalova, Rudi Sch\\\"afer and Thomas Guhr
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最新提交年份：
2014
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英文摘要：
We analyze the daily stock data of the Nasdaq Composite index in the 22-year period 1992-2013 and identify market states as clusters of correlation matrices with similar correlation structures. We investigate the stability of the correlation structure of each state by estimating the statistical fluctuations of correlations due to their non-stationarity. Our study is based on a random matrix approach recently introduced to model the non-stationarity of correlations by an ensemble of random matrices. This approach reduces the complexity of the correlated market to a single parameter which characterizes the fluctuations of the correlations and can be determined directly from the empirical return distributions. This parameter provides an insight into the stability of the correlation structure of each market state as well as into the correlation structure dynamics in the whole observation period. The analysis reveals an intriguing relationship between average correlation and correlation fluctuations. The strongest fluctuations occur during periods of high average correlation which is the case particularly in times of crisis.
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中文摘要：
我们分析了纳斯达克综合指数1992-2013年22年期间的每日股票数据，并将市场状态识别为具有类似相关结构的相关矩阵簇。我们通过估计由于非平稳性而产生的相关性的统计波动来研究每个状态的相关性结构的稳定性。我们的研究基于最近引入的一种随机矩阵方法，该方法通过一组随机矩阵来模拟相关性的非平稳性。这种方法将相关市场的复杂性降低为一个单一参数，该参数表征相关性的波动，并可直接从经验收益分布确定。该参数提供了对每个市场状态相关结构稳定性的洞察，以及对整个观察期内相关结构动态的洞察。分析揭示了平均相关性和相关性波动之间的有趣关系。最强的波动发生在平均相关性较高的时期，尤其是在危机时期。
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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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