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Review of Quantitative Finance and Accounting

, Volume 43, Issue 4, pp 751–779 | Cite as

A noise-robust estimator of volatility based on interquantile ranges

  • Jin-Huei Yeh
  • Jying-Nan Wang
  • Chung-Ming Kuan
Original Research
  • 213 Downloads

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.

Keywords

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

JEL Classification

G10 G12 C58 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of FinanceNational Central UniversityTaoyuanTaiwan
  2. 2.Department of FinanceMinghsin University of Science and TechnologyHsinchuTaiwan
  3. 3.Department of FinanceNational Taiwan UniversityTaipeiTaiwan

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