基于半鞅过程的中国股市随机波动、跳跃和微观结构噪声统计特征研究

doi:10.16381/j.cnki.issn1003-207x.2016.05.003

Abstract

Abstract: In this paper the different asymptotic behavior of the power variations is exploited as the power p, the truncation level and the sampling frequency are varying,and test statistics is developed on the realized power variation, then a systematic econometric analysis of stochastic volatility,jump and noise existing in high frequency financial returns is given based on Semimartingales Process, asset returns sampled at high frequency are decomposed into their base components (continuous, small jumps, large jumps), the relative magnitude of the components is determined, considering market microstructure noise. The methodology is applied to individual stock returns from different industries, those with different liquidity as well as stock index returns and its constituent stocks. Our results show that noisy traders exist widely in CSM; 43% risk results from stochastic volatility risk in asset return process, possibly hedged by equity option; the importance order of risk from different sources is stochastic volatility, systemic jump and heterogeneous jump; more liquid equities have more significant proof of jump, especially infinite small jumps.

Key words: high-frequency data, semimartingales, jump, noise, liquidity

CLC Number:

F830.9

LIU Zhi-dong, YAN Guan. Analysis of the Finer Statistical Characteristics of China Stock Market Based on Semimartingales Process[J]. Chinese Journal of Management Science, 2016, 24(5): 18-30.

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Analysis of the Finer Statistical Characteristics of China Stock Market Based on Semimartingales Process

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