Volatility occupation times

We propose nonparametric estimators of the occupation measure and the occupation density of the diffusion coefficient (stochastic volatility) of a discretely observed Itô semimartingale on a fixed interval when the mesh of the observation grid shrinks to zero asymptotically. In a first step we estim...

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Main Authors: LI, Jia, TODOROV, Viktor, TAUCHEN, George
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Language:English
Published: Institutional Knowledge at Singapore Management University 2013
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Online Access:https://ink.library.smu.edu.sg/soe_research/2569
https://ink.library.smu.edu.sg/context/soe_research/article/3568/viewcontent/Volatility_Occupation_Times.pdf
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spelling sg-smu-ink.soe_research-35682023-11-22T05:53:57Z Volatility occupation times LI, Jia TODOROV, Viktor TAUCHEN, George We propose nonparametric estimators of the occupation measure and the occupation density of the diffusion coefficient (stochastic volatility) of a discretely observed Itô semimartingale on a fixed interval when the mesh of the observation grid shrinks to zero asymptotically. In a first step we estimate the volatility locally over blocks of shrinking length, and then in a second step we use these estimates to construct a sample analogue of the volatility occupation time and a kernel-based estimator of its density. We prove the consistency of our estimators and further derive bounds for their rates of convergence. We use these results to estimate nonparametrically the quantiles associated with the volatility occupation measure. 2013-08-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/2569 info:doi/10.1214/13-AOS1135 https://ink.library.smu.edu.sg/context/soe_research/article/3568/viewcontent/Volatility_Occupation_Times.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University high-frequency data local approximation nonparametric estimation occupation time quantiles spot variance stochastic volatility Econometrics Economic Theory
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic high-frequency data
local approximation
nonparametric estimation
occupation time
quantiles
spot variance
stochastic volatility
Econometrics
Economic Theory
spellingShingle high-frequency data
local approximation
nonparametric estimation
occupation time
quantiles
spot variance
stochastic volatility
Econometrics
Economic Theory
LI, Jia
TODOROV, Viktor
TAUCHEN, George
Volatility occupation times
description We propose nonparametric estimators of the occupation measure and the occupation density of the diffusion coefficient (stochastic volatility) of a discretely observed Itô semimartingale on a fixed interval when the mesh of the observation grid shrinks to zero asymptotically. In a first step we estimate the volatility locally over blocks of shrinking length, and then in a second step we use these estimates to construct a sample analogue of the volatility occupation time and a kernel-based estimator of its density. We prove the consistency of our estimators and further derive bounds for their rates of convergence. We use these results to estimate nonparametrically the quantiles associated with the volatility occupation measure.
format text
author LI, Jia
TODOROV, Viktor
TAUCHEN, George
author_facet LI, Jia
TODOROV, Viktor
TAUCHEN, George
author_sort LI, Jia
title Volatility occupation times
title_short Volatility occupation times
title_full Volatility occupation times
title_fullStr Volatility occupation times
title_full_unstemmed Volatility occupation times
title_sort volatility occupation times
publisher Institutional Knowledge at Singapore Management University
publishDate 2013
url https://ink.library.smu.edu.sg/soe_research/2569
https://ink.library.smu.edu.sg/context/soe_research/article/3568/viewcontent/Volatility_Occupation_Times.pdf
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