高频波动率矩阵估计的比较分析——基于有噪非同步的金融数据

doi:10.16381/j.cnki.issn1003-207x.2015.10.003

Abstract

Abstract: High-frequency volatility matrix estimator can effectively solve some bottleneck problems faced by traditional low-frequency estimators. However, because of the influence of non-synchronous trading and market microstructure noise, it has epps effect and some big bias. So mainly three kinds of synchronization methods for non-synchronous step-by-step high-frequency data and five types of the noised-reduction methods for the traditional realized volatility matrix are considered in this paper. The two kinds of methods are deeply compared separately, from data simulation and empirical analysis. The results suggest that refresh time method includes the largest amount of data among methods we considered, realized volatility matrix has epps effect and serious bias, multivariate realized kernels, two scales realized volatility matrix estimator and modulated realized volatility matrix estimator effectively reduce noise, but pre-averaging HY and HY estimators behave a little bad. The research results can provide a useful reference and guidance on methods for workers in related fields of further research and application.

Key words: volatility matrix, high-frequency data, market microstructure noisy, non-synchronous trading

CLC Number:

F830.9

ZHAO Shu-ran, JIANG Ya-ping, REN Pen-min. Comparing Estimators of the High-Frequency Volatility Matrix in the Presence of Non-synchronous Trading and Market Microstructure Noise[J]. Chinese Journal of Management Science, 2015, 23(10): 19-29.

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Comparing Estimators of the High-Frequency Volatility Matrix in the Presence of Non-synchronous Trading and Market Microstructure Noise

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