Quarticity and other functionals of volatility: Efficient estimation

We consider a multidimensional Ito semimartingale regularly sampled on [0,t] at high frequency $1/Δ_n$, with $Δ_n$ going to zero. The goal of this paper is to provide an estimator for the integral over [0,t] of a given function of the volatility matrix. To approximate the integral, we simply use a Riemann sum based on local estimators of the pointwise volatility. We show that although the accuracy of the pointwise estimation is at most $Δ_n^{1/4}$, this procedure reaches the parametric rate $Δ_n^{1/2}$, as it is usually the case in integrated functionals estimation. After a suitable bias correction, we obtain an unbiased central limit theorem for our estimator and show that it is asymptotically efficient within some classes of sub models.

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