Optimal nonparametric range-based volatility estimation
We present a general framework for optimal nonparametric spot volatility estimation based on intraday range data, comprised of the first, highest, lowest, and last price over a given time-interval. We rely on a decision-theoretic approach together with a coupling-type argument to directly tailor the...
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2024
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sg-smu-ink.soe_research-36452023-11-09T07:49:53Z Optimal nonparametric range-based volatility estimation BOLLERSLEV, Tim LI, Jia LI, Qiyuan We present a general framework for optimal nonparametric spot volatility estimation based on intraday range data, comprised of the first, highest, lowest, and last price over a given time-interval. We rely on a decision-theoretic approach together with a coupling-type argument to directly tailor the form of the nonparametric estimator to the specific volatility measure of interest and relevant loss function. The resulting new optimal estimators offer substantial efficiency gains compared to existing commonly used range-based procedures. 2024-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/2646 info:doi/10.1016/j.jeconom.2023.105548 https://ink.library.smu.edu.sg/context/soe_research/article/3645/viewcontent/Decision_av_2023.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University spot volatility nonparametric estimation range-based estimation high-frequency data decision theory Econometrics Finance |
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Singapore Management University |
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SMU Libraries |
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Asia |
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Singapore Singapore |
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English |
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spot volatility nonparametric estimation range-based estimation high-frequency data decision theory Econometrics Finance |
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spot volatility nonparametric estimation range-based estimation high-frequency data decision theory Econometrics Finance BOLLERSLEV, Tim LI, Jia LI, Qiyuan Optimal nonparametric range-based volatility estimation |
| description |
We present a general framework for optimal nonparametric spot volatility estimation based on intraday range data, comprised of the first, highest, lowest, and last price over a given time-interval. We rely on a decision-theoretic approach together with a coupling-type argument to directly tailor the form of the nonparametric estimator to the specific volatility measure of interest and relevant loss function. The resulting new optimal estimators offer substantial efficiency gains compared to existing commonly used range-based procedures. |
| format |
text |
| author |
BOLLERSLEV, Tim LI, Jia LI, Qiyuan |
| author_facet |
BOLLERSLEV, Tim LI, Jia LI, Qiyuan |
| author_sort |
BOLLERSLEV, Tim |
| title |
Optimal nonparametric range-based volatility estimation |
| title_short |
Optimal nonparametric range-based volatility estimation |
| title_full |
Optimal nonparametric range-based volatility estimation |
| title_fullStr |
Optimal nonparametric range-based volatility estimation |
| title_full_unstemmed |
Optimal nonparametric range-based volatility estimation |
| title_sort |
optimal nonparametric range-based volatility estimation |
| publisher |
Institutional Knowledge at Singapore Management University |
| publishDate |
2024 |
| url |
https://ink.library.smu.edu.sg/soe_research/2646 https://ink.library.smu.edu.sg/context/soe_research/article/3645/viewcontent/Decision_av_2023.pdf |
| _version_ |
1783955667611025408 |