Realised Quantile-Based Estimation of the Integrated Variance
In this paper, we propose a new jump robust quantile-based realised variancemeasure of ex-post return variation that can be computed using potentially noisy data. This new estimator is consistent for integrated variance and we present feasible central limit theorems which show that it converges at the best attainable rate and has excellent efficiency. Asymptotically, the quantile-based realised variance is immune to finite activity jumps and outliers in the price series, while in modified form the estimator is applicable with market microstructure noise and therefore operational on highfrequency data. Simulations show that it also has superior robustness properties in finite samples, while an empirical application illustrates its use on equity data.
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