The '''realized kernel''' (RK) is an estimator of volatility. The estimator is typically computed with high frequency return data, such as second-by-second returns. Unlike the realized variance, the realized kernel is a robust estimator of volatility, in the sense that the realized kernel estimates the appropriate volatility quantity, even when the returns are contaminated with noise. <ref>{{Cite journal |last1=Barndorff-Nielsen |first1=Ole E. |last2=Hansen |first2=Peter Reinhard |last3=Lunde |first3=Asger |last4=Shephard |first4=Neil |authorlink=Ole Barndorff-Nielsen |authorlink2=Peter Reinhard Hansen |authorlink4=Neil Shephard |date=November 2008 |title=Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise |pages=1481–1536 |doi=10.3982/ECTA6495 |url=http://www.econometricsociety.org/abstract.asp?ref=0012-9682&vid=76&iid=6&aid=9&s=-9999 |journal=Econometrica |volume=76 |issue=6 |url-status=dead |archiveurl=https://web.archive.org/web/20110726230752/http://www.econometricsociety.org/abstract.asp?ref=0012-9682&vid=76&iid=6&aid=9&s=-9999 |archivedate=2011-07-26 |url-access=subscription }}</ref>
==Notes== {{Reflist}}
Category:Mathematical finance