Inference for Volatility Functionals of Itô Semimartingales Observed with Noise
This paper presents the nonparametric inference for nonlinear volatility functionals of general multivariate Itô semimartingales, in high-frequency and noisy setting. The estimator achieves the optimal convergence rate after explicit bias correction. A stable central limit theorem is attained with estimable asymptotic covariance matrix.
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