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摘要翻译：
我们提出了高频金融数据相关性失真的两个统计原因。我们证明了交易的非同步性以及股票价格的十进制对相关系数向更小的回报区间的下降有很大的影响（Epps效应）。这些扭曲取决于时间序列的性质，纯粹是统计起源。我们能够提出无参数补偿方法，我们在一个模型设置中进行了验证。此外，还将补偿方法应用于纽约证券交易所TAQ数据库的高频经验数据。Epps效应的一个主要部分可以得到补偿。对于低价交易的股票来说，所述原因的贡献尤其大。
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英文标题：
《Statistical causes for the Epps effect in microstructure noise》
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作者：
Michael C. M\"unnix, Rudi Sch\"afer, Thomas Guhr
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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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一级分类：Quantitative Finance 数量金融学
二级分类：Trading and Market Microstructure 交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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英文摘要：
We present two statistical causes for the distortion of correlations on high-frequency financial data. We demonstrate that the asynchrony of trades as well as the decimalization of stock prices has a large impact on the decline of the correlation coefficients towards smaller return intervals (Epps effect). These distortions depend on the properties of the time series and are of purely statistical origin. We are able to present parameter-free compensation methods, which we validate in a model setup. Furthermore, the compensation methods are applied to high-frequency empirical data from the NYSE's TAQ database. A major fraction of the Epps effect can be compensated. The contribution of the presented causes is particularly high for stocks that are traded at low prices.
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PDF链接：
https://arxiv.org/pdf/1009.6157
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