Edgeworth expansions for realized volatility and related estimators
This paper shows that the asymptotic normal approximation is often insufficiently accurate for volatility estimators based on high frequency data. To remedy this, we derive Edgeworth expansions for such estimators. The expansions are developed in the framework of small-noise asymptotics. The results have application to Cornish-Fisher inversion and help setting intervals more accurately than those relying on normal distribution.
Year of publication: |
2011
|
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Authors: | Zhang, Lan ; Mykland, Per A. ; Aït-Sahalia, Yacine |
Published in: |
Journal of Econometrics. - Elsevier, ISSN 0304-4076. - Vol. 160.2011, 1, p. 190-203
|
Publisher: |
Elsevier |
Keywords: | Bias correction Edgeworth expansion Market microstructure Martingale Realized volatility Two scales realized volatility |
Saved in:
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