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Jump-robust volatility estimation using nearest neighbor truncation

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Jump-robust volatility estimation using nearest neighbor truncation. / Andersen, T.G.; Dobrev, Dobrislav; Schaumburg, Ernst.

In: Journal of Econometrics, Vol. 169, No. 1, 01.07.2012, p. 75-93.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Harvard

Andersen, TG, Dobrev, D & Schaumburg, E 2012, 'Jump-robust volatility estimation using nearest neighbor truncation', Journal of Econometrics, vol. 169, no. 1, pp. 75-93. https://doi.org/10.1016/j.jeconom.2012.01.011

APA

CBE

MLA

Andersen, T.G., Dobrislav Dobrev and Ernst Schaumburg. "Jump-robust volatility estimation using nearest neighbor truncation". Journal of Econometrics. 2012, 169(1). 75-93. https://doi.org/10.1016/j.jeconom.2012.01.011

Vancouver

Author

Andersen, T.G. ; Dobrev, Dobrislav ; Schaumburg, Ernst. / Jump-robust volatility estimation using nearest neighbor truncation. In: Journal of Econometrics. 2012 ; Vol. 169, No. 1. pp. 75-93.

Bibtex

@article{b356625b0a834331810a149145aad6b0,
title = "Jump-robust volatility estimation using nearest neighbor truncation",
abstract = "We propose two new jump-robust estimators of integrated variance that allow for an asymptotic limit theory in the presence of jumps. Specifically, our MedRV estimator has better efficiency properties than the tripower variation measure and displays better finite-sample robustness to jumps and small ({"}zero{"}) returns. We stress the benefits of local volatility measures using short return blocks, as this greatly alleviates the downward biases stemming from rapid fluctuations in volatility, including diurnal (intraday) U-shape patterns. An empirical investigation of the Dow Jones 30 stocks and extensive simulations corroborate the robustness and efficiency properties of our nearest neighbor truncation estimators.",
author = "T.G. Andersen and Dobrislav Dobrev and Ernst Schaumburg",
year = "2012",
month = jul,
day = "1",
doi = "10.1016/j.jeconom.2012.01.011",
language = "English",
volume = "169",
pages = "75--93",
journal = "Journal of Econometrics",
issn = "0304-4076",
publisher = "Elsevier BV",
number = "1",

}

RIS

TY - JOUR

T1 - Jump-robust volatility estimation using nearest neighbor truncation

AU - Andersen, T.G.

AU - Dobrev, Dobrislav

AU - Schaumburg, Ernst

PY - 2012/7/1

Y1 - 2012/7/1

N2 - We propose two new jump-robust estimators of integrated variance that allow for an asymptotic limit theory in the presence of jumps. Specifically, our MedRV estimator has better efficiency properties than the tripower variation measure and displays better finite-sample robustness to jumps and small ("zero") returns. We stress the benefits of local volatility measures using short return blocks, as this greatly alleviates the downward biases stemming from rapid fluctuations in volatility, including diurnal (intraday) U-shape patterns. An empirical investigation of the Dow Jones 30 stocks and extensive simulations corroborate the robustness and efficiency properties of our nearest neighbor truncation estimators.

AB - We propose two new jump-robust estimators of integrated variance that allow for an asymptotic limit theory in the presence of jumps. Specifically, our MedRV estimator has better efficiency properties than the tripower variation measure and displays better finite-sample robustness to jumps and small ("zero") returns. We stress the benefits of local volatility measures using short return blocks, as this greatly alleviates the downward biases stemming from rapid fluctuations in volatility, including diurnal (intraday) U-shape patterns. An empirical investigation of the Dow Jones 30 stocks and extensive simulations corroborate the robustness and efficiency properties of our nearest neighbor truncation estimators.

UR - http://www.scopus.com/inward/record.url?scp=84861876025&partnerID=8YFLogxK

U2 - 10.1016/j.jeconom.2012.01.011

DO - 10.1016/j.jeconom.2012.01.011

M3 - Journal article

AN - SCOPUS:84861876025

VL - 169

SP - 75

EP - 93

JO - Journal of Econometrics

JF - Journal of Econometrics

SN - 0304-4076

IS - 1

ER -