流动性与市场微观结构噪声:来自佩考数据的证据

Małgorzata Doman
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引用次数: 5

摘要

超高频数据的可用性证明了在股票价格建模中使用连续时间方法的合理性。然而,这些数据除了包含有关价格过程的信息外,还包含导致已实现波动性偏差的微观结构噪声。这种噪音与贸易的所有现实都有关。在本文中,我们从价格过程中分离微观结构噪声,并以波兰Pekao S.A.公司的股票为例,确定了估计已实现波动率的噪声与信号之比,结果用于发现计算已实现波动率的最佳采样频率。此外,我们还检查了噪声与一些流动性措施之间的联系。
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Liquidity and Market Microstructure Noise: Evidence from the Pekao Data
The availability of ultra-high frequency data justifies the use of a continuous-time approach in stock prices modeling. However, this data contain, apart from the information about the price process, a microstructure noise causing a bias in the realized volatility. This noise is connected with all the reality of trade. In the paper we separate the microstructure noise from the price process and determine the noise to signal ratio for the estimates of the realized volatility in the case of the shares of the Polish company Pekao S.A. The results are used to discover the optimal sampling frequency for the realized volatility calculation. Moreover, we check the linkages between the noise and some liquidity measures.
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