资产专属限价订单微观结构噪声：参数估计与实证证据
Asset-specific limit order microstructure noise: Parameter estimation and empirical evidence
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中文总结 AI 辅助
该研究推广了限价订单簿高频报价的单边微观结构噪声模型，针对资产专属噪声尾部参数的估计建立了中心极限定理，并通过纳斯达克数据实证验证了该参数对有效价格及波动率估计的重要性。
中文摘要 AI 辅助
本文将限价订单簿高频报价的单边微观结构噪声模型进行了推广，以捕捉资产专属的噪声尾部行为。噪声尾部参数的估计成为推断的关键步骤，当指定参数化噪声模型时，这一估计可基于高频收益的矩来实现。对于Gamma噪声分布，我们针对由所得Gamma差分分布产生的1-相依观测值建立了中心极限定理，并证明该定理在具有一般半鞅对数价格动态的卷积模型中同样成立。我们强调，噪声尾部参数对有效价格及其波动率的估计具有重要影响。对近期纳斯达克限价订单簿数据的实证分析表明，资产专属噪声尾部参数在实际应用中具有相关性。
英文摘要
The one-sided microstructure noise model for high-frequency quotes from a limit order book is generalized to capture asset-specific noise tail behaviour. Estimation of a noise tail parameter becomes the key step for inference. This is possible based on moments of the high-frequency returns when specifying a parametric noise model. For a Gamma noise distribution, we establish a central limit theorem for 1-dependent observations from the resulting Gamma difference distribution and prove that it is valid also in the convolution model with general semimartingale log-price dynamics. We highlight that the noise tail parameter has important implications for estimating the efficient price and its volatility. An empirical analysis of recent NASDAQ limit order book data demonstrates that asset-specific noise tail parameters are relevant in practice.
