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微观结构噪声与埃普斯效应的收益模型

文章 arXiv papers · 作者: A. Saichev et al.
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总结

本文提出一种逐笔金融收益模型，将 ARFIMA 过程、买卖价反弹、肥尾收益和非泊松交易间隔结合起来，用于解释市场数据中的若干特征：短暂的收益相关性、持续时间更长的绝对收益相关性、微观结构噪声和埃普斯效应。

在模型中，买卖价反弹会产生负收益相关性，有助于解释为什么测量间隔越长，波动率估计越低。埃普斯效应——即测得的跨资产相关性随间隔延长而上升——被归因于这样一种统计重叠：资产确实存在相关性，且收益呈现长记忆时，收益动量会发生重叠。文中将此作为定性和定量解释，但所提供文本未给出数据集、参数估计或与其他解释的比较，因此无法据此判断该模型适用于不同市场的程度。

核心观点

  • 该模型结合长记忆收益、买卖价反弹、肥尾和非泊松交易时序。
  • 买卖价反弹会引入短期负收益相关性。
  • 随着收益估计间隔增大，测得的波动率可能下降。
  • 测得的跨资产相关性可能随间隔延长而上升，形成埃普斯效应。
  • 当资产确实存在相关性时，长记忆动量重叠被作为埃普斯效应的一种可能解释。

标签

市场微观结构统计学波动率高频交易
全文
# A simple microstructure return model explaining microstructure noise and Epps effects


# A simple microstructure return model explaining microstructure noise and Epps effects









We present a 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 microstructure 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. Paradoxically, 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).

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。