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A simple microstructure return model explaining microstructure noise and Epps effects

机译:一个简单的微观结构返回模型,解释微观结构噪声和Epps效应

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摘要

We present a novel simple microstructure model of financial returns that combines (i) the well-known ARFIMA process applied to tick-by-tick returns, (ii) the bid-ask bounce effect, (iii) the fat tail structure of the distribution of returns and (iv) the non-Poissonian statistics of inter-trade intervals. This model allows us to explain both qualitatively and quantitatively important stylized facts observed in the statistics of both microstructure and macrostructure returns, including the short-ranged correlation of returns, the long-ranged correlations of absolute returns, the microstructure noise and Epps effects. According to the microstructure noise effect, volatility is a decreasing function of the time-scale used to estimate it. The Epps effect states that cross correlations between asset returns are increasing functions of the time-scale at which the returns are estimated. The microstructure noise is explained as the result of the negative return correlations inherent in the definition of the bid-ask bounce component (ii). In the presence of a genuine correlation between the returns of two assets, the Epps effect is due to an average statistical overlap of the momentum of the returns of the two assets defined over a finite time-scale in the presence of the long memory process (i).
机译:我们提供了一种新颖的简单的财务收益微观结构模型,该模型结合了(i)应用于逐笔收益的著名ARFIMA流程,(ii)买入/卖出反弹效应,(iii)分布的胖尾结构(iv)交易间隔的非泊松统计。该模型使我们能够解释在微观结构和宏观结构收益的统计数据中观察到的定性和定量重要的程式化事实,包括收益的短期相关性,绝​​对收益的长期相关性,微观结构噪声和Epps效应。根据微结构噪声效应,挥发性是用于估计它的时间尺度的递减函数。 Epps效应表明,资产收益率之间的相互关系是估算收益率的时间尺度的递增函数。解释微结构噪声是由于出价跳动分量(ii)定义固有的负回报相关性的结果。如果两种资产的收益之间存在真正的相关性,那么Epps效应是由于在存在长记忆过程的情况下,在有限的时间范围内定义的两种资产的收益动量的平均统计重叠(一世)。

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