摘要翻译:
本文提出了一种在计算异步时间序列相关性时对统计误差进行补偿的方法。该方法基于一个潜在时间序列的假设。我们建立了一个模型,并将其应用于金融数据,以检验计算的相关性对较小回报间隔的减少(Epps效应)。我们表明,这种统计效应是Epps效应的主要原因。因此,我们能够量化和补偿它只使用交易价格和交易时间。
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英文标题:
《Compensating asynchrony effects in the calculation of financial
correlations》
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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 a method to compensate statistical errors in the calculation of correlations on asynchronous time series. The method is based on the assumption of an underlying time series. We set up a model and apply it to financial data to examine the decrease of calculated correlations towards smaller return intervals (Epps effect). We show that this statistical effect is a major cause of the Epps effect. Hence, we are able to quantify and to compensate it using only trading prices and trading times.
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PDF链接:
https://arxiv.org/pdf/0910.2909