Large Deviation Principles of Realized Laplace Transform of Volatility

被引：0

作者：

Feng, Xinwei ^{[1
]}

He, Lidan ^{[2
]}

Liu, Zhi ^{[3
]}

机构：

[1] Shandong Univ, Zhongtai Secur Inst Financial Studies, Jinan, Shandong, Peoples R China

[2] Univ Macau, Macau, Peoples R China

[3] Zhuhai UM Sci & Technol Res Inst, Zhuhai, Peoples R China

来源：

JOURNAL OF THEORETICAL PROBABILITY | 2022年 / 35卷 / 01期

基金：

中国国家自然科学基金;

关键词：

High-frequency data; Realized Laplace transform of volatility; Semi-martingale; Large deviation; Moderate deviation; MODERATE DEVIATIONS; SEMIMARTINGALES; ESTIMATORS; DIFFUSION; INFERENCE;

D O I：

10.1007/s10959-020-01055-4

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Under the scenario of high-frequency data, a consistent estimator of the realized Laplace transform of volatility is proposed by Todorov and Tauchen (Econometrica 80:1105-1127, 2012) and a related central limit theorem has been well established. In this paper, we investigate the asymptotic tail behaviour of the empirical realized Laplace transform of volatility (ERLTV). We establish both a large deviation principle and a moderate deviation principle for the ERLTV. The good rate function for the large deviation principle is well defined in the whole real space, which indicates a limit for the normalized logarithmic tail probability of the ERLTV. Moreover, we also derive the function-level large and moderate deviation principles for ERLTV.

引用

页码：186 / 208

页数：23

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