Edgeworth Expansions for Realized Volatility and Related Estimators ∗

  title={Edgeworth Expansions for Realized Volatility and Related Estimators ∗},
  author={Lan Zhang and Per Aslak Mykland},
This paper shows that the asymptotic normal approximation is often insufficiently accurate for volatility estimators based on high frequency data. To remedy this, we compute Edgeworth expansions for such estimators. Unlike the usual expansions, we have found that in order to obtain meaningful terms, one needs to let the size of the noise to go zero asymptotically. The results have application to Cornish-Fisher inversion and bootstrapping. 
Highly Cited
This paper has 23 citations. REVIEW CITATIONS
17 Citations
22 References
Similar Papers


Publications referenced by this paper.
Showing 1-10 of 22 references

An Introduction to Probability Theory and Its Applications, Volume 2

  • W. Feller
  • 1971
Highly Influential
6 Excerpts

2005a): “How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise,

  • Y. Aït-Sahalia, P. A. Mykland, L. Zhang
  • Review of Financial Studies,
  • 2005
Highly Influential
2 Excerpts

Tensor Methods in Statistics

  • P. McCullagh
  • 1987
Highly Influential
3 Excerpts

A Tale of Two Time Scales: Determining Integrated Volatility with Noisy High-Frequency Data,

  • L. Zhang, P. A. Mykland
  • Aït-Sahalia
  • 2002

Similar Papers

Loading similar papers…