A Noise-Robust Estimator of Volatility Based on Interquantile Ranges

Abstract

This paper proposes a new class of estimators based on the inter-quantile-range of intraday returns, referred to as Inter-Quantile-Range-based volatility (IQRBV), to estimate the integrated daily volatility. As the range-based volatility measure, the IQRBV estimate is insensitive to market microstructure noises. More importantly and intuitively, it is shown that a properly chosen IQRBV is also jump-free for its trimming of the intraday extreme two tails by utilizing the range between the symmetric quantiles. We exploit its approximation optimality by examining a general class of distributions from the Pearson type IV family and recommend using IQRBV.04 as the integrated variance estimate. Both our simulation and the empirical results highlight the interesting features of the easy-to-implement and model-free IQRBV over the other competing estimators that are seen in the literature.