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...
Saved in:
Main Authors: | , , |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2021
|
Subjects: | |
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 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
id |
sg-smu-ink.soe_research-3552 |
---|---|
record_format |
dspace |
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 |
_version_ |
1770576090770702336 |