Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5096773 | Journal of Econometrics | 2011 | 14 Pages |
Abstract
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.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Lan Zhang, Per A. Mykland, Yacine Aït-Sahalia,