| 具有舍入误差微观结构噪音高频数据的杠杆效应分析 |
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| 引用本文： | 蔺富明,周勇.具有舍入误差微观结构噪音高频数据的杠杆效应分析[J].应用数学学报,2021(1):16-30. |
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| 作者姓名： | 蔺富明 周勇 |
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| 作者单位： | 上海财经大学统计与管理学院;四川轻化工大学数学与统计学院;统计与数据科学前沿理论及应用教育部重点实验室华东师范大学统计交叉科学研究院 |
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| 基金项目： | 国家自然科学基金委重点项目(No.71931004);重大研究计划培育项目(No.92046005);桥梁无损检测四川省高校重点实验室项目(No.2018QZJ01);四川轻化工大学人才引进项目(No.2019RC10)资助。 |
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| 摘 要： | 本杠杆效应反映了股票收益率与其波动率变动之间的负相关关系,它一直是金融研究的核心问题.在高频时间序列数据中,传统的简单相关系数估计是不相合的,为此一些学者给出了新的杠杆效应刻画-积分杠杆效应,并给出该杠杆效应的估计量.众所周知,高频数据易受市场微观结构噪音的干扰,其中舍入误差是非常重要、实际中普遍存在的一类.高频数据被舍入误差噪音污染后,本文研究上述学者提出的杠杆效应估计量的稳健性,获得杠杆效应估计的相合性及渐近正态性,并用随机模拟对结果进行了验证.
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| 关 键 词： | 高频数据 杠杆效应 杠杆效应估计量 市场微观结构噪音 舍入误差噪音 |
Analysis of Leverage Effect Based on High Frequency Data with Rounding Error Market Microstructure Noise |
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| LIN FUMING,ZHOU YONG.Analysis of Leverage Effect Based on High Frequency Data with Rounding Error Market Microstructure Noise[J].Acta Mathematicae Applicatae Sinica,2021(1):16-30. |
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| Authors: | LIN FUMING ZHOU YONG |
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| Institution: | (School of Statistics and Management,Shanghai University of Finance and Economics,Shanghai 200433,China;School of Mathematics and Statistics,Sichuan University of Science&Engineering,Zigong 643000,China;Key Laboratory of Advanced Theory an Application in Statistics and Data Science,MOE,and Academy of Statistics and Intendisciplinary Sciences and School of Statistics,East China Normal University,Shanghai 200062,China) |
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| Abstract: | The negative correlations between stock returns and their volatility changes are called the leverage effect,which is a core issue in financial research.Because the common simple correlation coefficient isn’t consistent any more in the context of high frequency data,some researchers proposed a new characterization of leverage effect:the integrated leverage effect and its estimators as well.As is well-known,high frequency data are too apt to be contaminated by market microstructure noise.Rounding is a crucial source of market microstructure noise and is the common phenomena in stock returns data.Based the rounding-error-contaminated high frequency data,the paper studies the robustness of the estimator of the integrated leverage effect and deduces its consistency and asymptotic normality.Furthermore,simulations illustrate our theoretical results. |
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| Keywords: | high frequency data leverage effect estimator of leverage effect market microstructure noise rounding error noise |
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