On the estimation of leverage effect and volatility of volatility in the presence of jumps

Fuente: arXiv
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Autori principali: Liu, Qiang, Liu, Zhi, Zhou, Wang
Natura: Preprint
Pubblicazione: 2025
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author Liu, Qiang
Liu, Zhi
Zhou, Wang
author_facet Liu, Qiang
Liu, Zhi
Zhou, Wang
contents We study the estimation of leverage effect and volatility of volatility by using high-frequency data with the presence of jumps. We first construct spot volatility estimator by using the empirical characteristic function of the high-frequency increments to deal with the effect of jumps, based on which the estimators of leverage effect and volatility of volatility are proposed. Compared with existing estimators, our method is valid under more general jumps, making it a better alternative for empirical applications. Under some mild conditions, the asymptotic normality of the estimators is established and consistent estimators of the limiting variances are proposed based on the estimation of volatility functionals. We conduct extensive simulation study to verify the theoretical results. The results demonstrate that our estimators have relative better performance than the existing ones, especially when the jump is of infinite variation. Besides, we apply our estimators to a real high-frequency dataset, which reveals nonzero leverage effect and volatility of volatility in the market.
format Preprint
id arxiv_https___arxiv_org_abs_2511_00944
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle On the estimation of leverage effect and volatility of volatility in the presence of jumps
Liu, Qiang
Liu, Zhi
Zhou, Wang
Methodology
Econometrics
We study the estimation of leverage effect and volatility of volatility by using high-frequency data with the presence of jumps. We first construct spot volatility estimator by using the empirical characteristic function of the high-frequency increments to deal with the effect of jumps, based on which the estimators of leverage effect and volatility of volatility are proposed. Compared with existing estimators, our method is valid under more general jumps, making it a better alternative for empirical applications. Under some mild conditions, the asymptotic normality of the estimators is established and consistent estimators of the limiting variances are proposed based on the estimation of volatility functionals. We conduct extensive simulation study to verify the theoretical results. The results demonstrate that our estimators have relative better performance than the existing ones, especially when the jump is of infinite variation. Besides, we apply our estimators to a real high-frequency dataset, which reveals nonzero leverage effect and volatility of volatility in the market.
title On the estimation of leverage effect and volatility of volatility in the presence of jumps
topic Methodology
Econometrics
url https://arxiv.org/abs/2511.00944