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 CornishFisher inversion and help setting intervals more accurately than those relying on normal distribution.
All Science Journal Classification (ASJC) codes
- Economics and Econometrics
- Bias correction
- Edgeworth expansion
- Market microstructure
- Realized volatility
- Two scales realized volatility