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Distribution-free specification test for volatility function based on high-frequency data with microstructure noise
Metrika ( IF 0.7 ) Pub Date : 2022-01-03 , DOI: 10.1007/s00184-021-00857-8
Yinfen Tang 1 , Tao Su 2 , Zhiyuan Zhang 2
Affiliation  

In this paper, we propose a two-step test for parametric specification of volatility function based on high-frequency data with microstructure noise. The latent prices are first recovered at high precision under the assumption that the noise is a parametric function of observable trading information. An asymptotically distribution-free test is then built on the estimated latent prices using Khmaladze martingale transformation. We establish asymptotic theory associated with the test under both the null and alternative hypotheses. Moreover, an extension of the proposed method to incorporate intraday pattern is also formally discussed. Simulation results corroborate our theoretical findings demonstrating clear advantage of our method over an existing distribution-free method that does not take microstructure noise into account. We finally apply the test to the high-frequency data of Standard & Poor’s depository receipt (SPDR) that tracks the S&P 500 index.



中文翻译:

基于高频数据的微结构噪声波动率函数无分布规范检验

在本文中,我们提出了一种基于具有微观结构噪声的高频数据的波动率函数参数规范的两步检验。在假设噪声是可观察交易信息的参数函数的情况下,首先以高精度恢复潜在价格。然后使用 Khmaladze martingale 变换在估计的潜在价格上建立渐近无分布测试。我们在原假设和替代假设下建立了与检验相关的渐近理论。此外,还正式讨论了将提议的方法扩展到合并日内模式。模拟结果证实了我们的理论发现,证明了我们的方法明显优于现有的不考虑微结构噪声的无分布方法。

更新日期:2022-01-03
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