英文标题：
《Cross-correlation asymmetries and causal relationships between stock and
market risk》
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作者：
Stanislav S. Borysov, Alexander V. Balatsky
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最新提交年份：
2014
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英文摘要：
We study historical correlations and lead-lag relationships between individual stock risk (volatility of daily stock returns) and market risk (volatility of daily returns of a market-representative portfolio) in the US stock market. We consider the cross-correlation functions averaged over all stocks, using 71 stock prices from the Standard \\& Poor\'s 500 index for 1994--2013. We focus on the behavior of the cross-correlations at the times of financial crises with significant jumps of market volatility. The observed historical dynamics showed that the dependence between the risks was almost linear during the US stock market downturn of 2002 and after the US housing bubble in 2007, remaining on that level until 2013. Moreover, the averaged cross-correlation function often had an asymmetric shape with respect to zero lag in the periods of high correlation. We develop the analysis by the application of the linear response formalism to study underlying causal relations. The calculated response functions suggest the presence of characteristic regimes near financial crashes, when the volatility of an individual stock follows the market volatility and vice versa.
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中文摘要：
我们研究了美国股市中单个股票风险（每日股票收益的波动性）和市场风险（具有市场代表性的投资组合的每日收益的波动性）之间的历史相关性和超前-滞后关系。我们考虑所有股票的平均互相关函数，使用标准普尔500指数1994-2013年的71个股票价格。我们关注的是在市场波动性大幅上升的金融危机时期相互关联的行为。观察到的历史动态表明，在2002年美国股市低迷期间和2007年美国房地产泡沫之后，风险之间的依赖性几乎是线性的，直到2013年都保持在这个水平。此外，在高相关性期间，平均互相关函数相对于零滞后通常具有不对称形状。我们通过应用线性响应形式主义来研究潜在的因果关系。计算出的响应函数表明，当单个股票的波动性跟随市场波动性，反之亦然时，金融崩溃附近存在特征性机制。
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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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