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基于中国股市逐笔交易数据,有效利用全样本不规则采样数据,对日内高频微观结构噪音的估计、特性及影响因素进行了研究。结果显示噪音分布具有尖峰厚尾的特点,日内模式呈现“L”型。信息非对称程度和流动性作为影响噪音的两个最重要因素,分别与噪音呈正相关和负相关关系。价差由于同时包含了信息非对称程度和流动性两方面的信息,对噪音有近60%的解释能力。
Based on the transaction-by-transaction data of China’s stock market, the irregular sample data of the whole sample is effectively used to study the estimation, characteristics and influencing factors of the high-frequency microstructure noise in Japan. The results show that the noise distribution has the characteristics of a sharp tail and a thick tail, and the intraday pattern shows a “L” shape. As the two most important factors that affect noise, the degree of information asymmetry and liquidity are respectively positively and negatively correlated with the noise. Spreads contain nearly 60% of the noise as a result of both asymmetric information and liquidity.