Volatility coupling

This paper provides a strong approximation, or coupling, theory for spot volatility estimators formed using high-frequency data. We show that the t-statistic process associated with the nonparametric spot volatility estimator can be strongly approximated by a growing-dimensional vector of independen...

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Main Authors: JACOD, Jean, LI, Jia, LIAO, Zhipeng
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2021
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Online Access:https://ink.library.smu.edu.sg/soe_research/2553
https://ink.library.smu.edu.sg/context/soe_research/article/3552/viewcontent/vc.pdf
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spelling sg-smu-ink.soe_research-35522022-02-07T04:37:55Z Volatility coupling JACOD, Jean LI, Jia LIAO, Zhipeng This paper provides a strong approximation, or coupling, theory for spot volatility estimators formed using high-frequency data. We show that the t-statistic process associated with the nonparametric spot volatility estimator can be strongly approximated by a growing-dimensional vector of independent variables defined as functions of Brownian increments. We use this coupling theory to study the uniform inference for the volatility process in an infill asymptotic setting. Specifically, we propose uniform confidence bands for spot volatility, beta, idiosyncratic variance processes, and their nonlinear transforms. The theory is also applied to address an open question concerning the inference of monotone nonsmooth integrated volatility functionals such as the occupation time and its quantiles. 2021-08-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/2553 info:doi/10.1214/20-AOS2023 https://ink.library.smu.edu.sg/context/soe_research/article/3552/viewcontent/vc.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Econometrics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Econometrics
spellingShingle Econometrics
JACOD, Jean
LI, Jia
LIAO, Zhipeng
Volatility coupling
description This paper provides a strong approximation, or coupling, theory for spot volatility estimators formed using high-frequency data. We show that the t-statistic process associated with the nonparametric spot volatility estimator can be strongly approximated by a growing-dimensional vector of independent variables defined as functions of Brownian increments. We use this coupling theory to study the uniform inference for the volatility process in an infill asymptotic setting. Specifically, we propose uniform confidence bands for spot volatility, beta, idiosyncratic variance processes, and their nonlinear transforms. The theory is also applied to address an open question concerning the inference of monotone nonsmooth integrated volatility functionals such as the occupation time and its quantiles.
format text
author JACOD, Jean
LI, Jia
LIAO, Zhipeng
author_facet JACOD, Jean
LI, Jia
LIAO, Zhipeng
author_sort JACOD, Jean
title Volatility coupling
title_short Volatility coupling
title_full Volatility coupling
title_fullStr Volatility coupling
title_full_unstemmed Volatility coupling
title_sort volatility coupling
publisher Institutional Knowledge at Singapore Management University
publishDate 2021
url https://ink.library.smu.edu.sg/soe_research/2553
https://ink.library.smu.edu.sg/context/soe_research/article/3552/viewcontent/vc.pdf
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