A noise-robust estimator of volatility based on interquantile ranges
Abstract This paper proposes a new class of estimators based on the interquantile range of intraday returns, referred to as interquantile range based volatility (IQRBV), to estimate the integrated daily volatility. More importantly and intuitively, it is shown that a properly chosen IQRBV is jump-fr...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Yeh, Jin-Huei [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media New York 2013 |
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| Übergeordnetes Werk: |
Enthalten in: Review of quantitative finance and accounting - Springer US, 1991, 43(2013), 4 vom: 02. Aug., Seite 751-779 |
|---|---|
| Übergeordnetes Werk: |
volume:43 ; year:2013 ; number:4 ; day:02 ; month:08 ; pages:751-779 |
| Links: |
|---|
| DOI / URN: |
10.1007/s11156-013-0391-7 |
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OLC2037191243 |
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| 520 | |a Abstract This paper proposes a new class of estimators based on the interquantile range of intraday returns, referred to as interquantile range based volatility (IQRBV), to estimate the integrated daily volatility. More importantly and intuitively, it is shown that a properly chosen IQRBV is jump-free for its trimming of the intraday extreme two tails that utilize the range between symmetric quantiles. We exploit its approximation optimality by examining a general class of distributions from the Pearson type IV family and recommend using $ IQRBV^{.04} $ as the integrated variance estimate. Both our simulation and the empirical results highlight interesting features of the easy-to-implement and model-free IQRBV over the other competing estimators that are seen in the literature. | ||
| 650 | 4 | |a Inter quantile range | |
| 650 | 4 | |a Price jump | |
| 650 | 4 | |a Realized volatility | |
| 650 | 4 | |a Range-based volatility | |
| 650 | 4 | |a Bi-power variation | |
| 650 | 4 | |a Market microstructure noise | |
| 700 | 1 | |a Wang, Jying-Nan |4 aut | |
| 700 | 1 | |a Kuan, Chung-Ming |4 aut | |
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10.1007/s11156-013-0391-7 doi (DE-627)OLC2037191243 (DE-He213)s11156-013-0391-7-p DE-627 ger DE-627 rakwb eng 650 330 VZ 3,2 ssgn Yeh, Jin-Huei verfasserin aut A noise-robust estimator of volatility based on interquantile ranges 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2013 Abstract This paper proposes a new class of estimators based on the interquantile range of intraday returns, referred to as interquantile range based volatility (IQRBV), to estimate the integrated daily volatility. More importantly and intuitively, it is shown that a properly chosen IQRBV is jump-free for its trimming of the intraday extreme two tails that utilize the range between symmetric quantiles. We exploit its approximation optimality by examining a general class of distributions from the Pearson type IV family and recommend using $ IQRBV^{.04} $ as the integrated variance estimate. Both our simulation and the empirical results highlight interesting features of the easy-to-implement and model-free IQRBV over the other competing estimators that are seen in the literature. Inter quantile range Price jump Realized volatility Range-based volatility Bi-power variation Market microstructure noise Wang, Jying-Nan aut Kuan, Chung-Ming aut Enthalten in Review of quantitative finance and accounting Springer US, 1991 43(2013), 4 vom: 02. Aug., Seite 751-779 (DE-627)170660036 (DE-600)1087855-5 (DE-576)029154634 0924-865X nnns volume:43 year:2013 number:4 day:02 month:08 pages:751-779 https://doi.org/10.1007/s11156-013-0391-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW GBV_ILN_26 GBV_ILN_32 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4125 AR 43 2013 4 02 08 751-779 |
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A noise-robust estimator of volatility based on interquantile ranges |
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Abstract This paper proposes a new class of estimators based on the interquantile range of intraday returns, referred to as interquantile range based volatility (IQRBV), to estimate the integrated daily volatility. More importantly and intuitively, it is shown that a properly chosen IQRBV is jump-free for its trimming of the intraday extreme two tails that utilize the range between symmetric quantiles. We exploit its approximation optimality by examining a general class of distributions from the Pearson type IV family and recommend using $ IQRBV^{.04} $ as the integrated variance estimate. Both our simulation and the empirical results highlight interesting features of the easy-to-implement and model-free IQRBV over the other competing estimators that are seen in the literature. © Springer Science+Business Media New York 2013 |
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Abstract This paper proposes a new class of estimators based on the interquantile range of intraday returns, referred to as interquantile range based volatility (IQRBV), to estimate the integrated daily volatility. More importantly and intuitively, it is shown that a properly chosen IQRBV is jump-free for its trimming of the intraday extreme two tails that utilize the range between symmetric quantiles. We exploit its approximation optimality by examining a general class of distributions from the Pearson type IV family and recommend using $ IQRBV^{.04} $ as the integrated variance estimate. Both our simulation and the empirical results highlight interesting features of the easy-to-implement and model-free IQRBV over the other competing estimators that are seen in the literature. © Springer Science+Business Media New York 2013 |
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Abstract This paper proposes a new class of estimators based on the interquantile range of intraday returns, referred to as interquantile range based volatility (IQRBV), to estimate the integrated daily volatility. More importantly and intuitively, it is shown that a properly chosen IQRBV is jump-free for its trimming of the intraday extreme two tails that utilize the range between symmetric quantiles. We exploit its approximation optimality by examining a general class of distributions from the Pearson type IV family and recommend using $ IQRBV^{.04} $ as the integrated variance estimate. Both our simulation and the empirical results highlight interesting features of the easy-to-implement and model-free IQRBV over the other competing estimators that are seen in the literature. © Springer Science+Business Media New York 2013 |
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A noise-robust estimator of volatility based on interquantile ranges |
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Wang, Jying-Nan Kuan, Chung-Ming |
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