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首页> 外文期刊>Physica, A. Statistical mechanics and its applications >Statistical properties, dynamic conditional correlation and scaling analysis: Evidence from Dow Jones and Nasdaq high-frequency data
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Statistical properties, dynamic conditional correlation and scaling analysis: Evidence from Dow Jones and Nasdaq high-frequency data

机译：统计属性，动态条件相关性和标度分析：来自道琼斯和纳斯达克高频数据的证据

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摘要

This paper investigates statistical properties of high-frequency intraday stock returns across various frequencies. Both time series and panel data are utilized to explore the properties of probability distribution, dynamic conditional correlations, and scaling analysis in Dow Jones Industrial Average (DJIA) and Nasdaq intraday returns across 10-min, 30-min, 60-min, 120-min, and 390-min frequencies. The evidence shows that both returns and volatility (standard deviation) increase with the increasing scaling from 10-min to 390-min intervals. By fitting an AR(1)-GARCH(1,1) model to intraday data, we find that AR(1) coefficients are negative for DJIA returns and positive for Nasdaq, exhibiting a positive and negative feedback strategy in DJIA and Nasdaq, respectively. The evidence also shows that these coefficients are statistically significant for either including or excluding opening returns for the 10-min and 30-min frequencies. By examining the dynamic conditional correlation between the DJIA and the Nasdaq across different frequencies, a positive correlation ranging from 0.6 to 0.8 was found. In addition, the variance of the dynamic correlation coefficients is decreasing and appears to be stable for the 2001-2003 period. Finally, both returns on DJIA and Nasdaq satisfy the stable Levy distributions, implying that both markets can converge to equilibrium by self-governing mechanism after shocks. Results of this work provide relevant implications for investors and policy makers.
机译：本文研究了各种频率下高频日内股票收益的统计特性。时间序列和面板数据均被用来探索概率分布，动态条件相关性以及道琼斯工业平均指数（DJIA）和纳斯达克盘中10分钟，30分钟，60分钟，120分钟和390分钟的频率。证据表明，收益率和波动率（标准差）都随着时间间隔从10分钟到390分钟的增加而增加。通过将AR（1）-GARCH（1,1）模型拟合到日内数据，我们发现AR（1）系数对DJIA收益为负，对纳斯达克为正，分别在DJIA和纳斯达克表现出正反馈和负反馈策略。证据还表明，对于包括或不包括10分钟和30分钟频率的开盘收益，这些系数具有统计学意义。通过检查DJIA和纳斯达克在不同频率之间的动态条件相关性，发现正相关性介于0.6到0.8之间。此外，动态相关系数的方差正在减小，并且在2001-2003年期间似乎是稳定的。最后，道琼斯工业平均指数和纳斯达克指数的收益均满足稳定的利维分布，这意味着两个市场在遭受冲击后可以通过自治机制收敛至均衡。这项工作的结果为投资者和决策者提供了相关的启示。

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