A noise-robust estimator of volatility based on interquantile ranges

Jin Huei Yeh, Jying Nan Wang, Chung Ming Kuan

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This paper proposes a new class of estimators based on the interquantile range of intraday returns, referred to as interquantile range based volatility (IQRBV), to estimate the integrated daily volatility. More importantly and intuitively, it is shown that a properly chosen IQRBV is jump-free for its trimming of the intraday extreme two tails that utilize the range between 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 interesting features of the easy-to-implement and model-free IQRBV over the other competing estimators that are seen in the literature.

Original languageEnglish
Pages (from-to)751-779
Number of pages29
JournalReview of Quantitative Finance and Accounting
Volume43
Issue number4
DOIs
StatePublished - Nov 2014

Keywords

  • Bi-power variation
  • Inter quantile range
  • Market microstructure noise
  • Price jump
  • Range-based volatility
  • Realized volatility

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