Realized kernel

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. [1]

Notes

Barndorff-Nielsen, Ole E.; Hansen, Peter Reinhard; Lunde, Asger; Shephard, Neil (November 2008). "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise". Econometrica. 76: 1481–1536. doi:10.3982/ECTA6495. Archived from the original on 2011-07-26.

gollark: Except not really that either and mapping on regular computers to it is kind of unhelpful.

gollark: The brain is combined kind-of-volatile RAM and CPU.

gollark: No, analogising it that way is ridiculous.

gollark: It's some sort of neural-net-type thing with weird extra communication between components running on weird hardware.

gollark: What if someone is, say, simulating the entire physical universe including my brain?

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[1] Barndorff-Nielsen, Ole E.; Hansen, Peter Reinhard; Lunde, Asger; Shephard, Neil (November 2008). "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise". Econometrica. 76: 1481–1536. doi:10.3982/ECTA6495. Archived from the original on 2011-07-26.