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Efficient multipowers

Kolokolov, Aleksey LU and Reno, Roberto (2016) In Working Papers in Statistics
Abstract
We show how to minimize the asymptotic variance of multipower estimators using a linear combination of optimal powers. Taking advantage of the lower variance provided by this technique allows to build superior estimators of integrated volatility powers. In particular, we focus on a new efficient quarticity estimator and we show, using simulated data, that we can drastically reduce the mean square error of traditional estimators. The implementation on US stock prices corroborates our theoretical findings and further shows that ecient quarticity noticeably reduces the number of detected jumps, and improves the quality of volatility forecasts.
Please use this url to cite or link to this publication:
author
and
publishing date
type
Working paper/Preprint
publication status
published
subject
keywords
Efficiency, Volatility, Jumps, Quarticity, Multipower, Threshold
in
Working Papers in Statistics
issue
2016:2
pages
43 pages
publisher
Department of Statistics, Lund university
language
English
LU publication?
no
id
b5d16157-c2e9-4849-8e19-ee550d27475f
date added to LUP
2016-09-21 13:18:43
date last changed
2018-11-21 21:26:02
@misc{b5d16157-c2e9-4849-8e19-ee550d27475f,
  abstract     = {{We show how to minimize the asymptotic variance of multipower estimators using a linear combination of optimal powers. Taking advantage of the lower variance provided by this technique allows to build superior estimators of integrated volatility powers. In particular, we focus on a new efficient quarticity estimator and we show, using simulated data, that we can drastically reduce the mean square error of traditional estimators. The implementation on US stock prices corroborates our theoretical findings and further shows that ecient quarticity noticeably reduces the number of detected jumps, and improves the quality of volatility forecasts.}},
  author       = {{Kolokolov, Aleksey and Reno, Roberto}},
  keywords     = {{Efficiency; Volatility; Jumps; Quarticity; Multipower; Threshold}},
  language     = {{eng}},
  note         = {{Working Paper}},
  number       = {{2016:2}},
  publisher    = {{Department of Statistics, Lund university}},
  series       = {{Working Papers in Statistics}},
  title        = {{Efficient multipowers}},
  url          = {{https://lup.lub.lu.se/search/files/12781772/16156_41326_1_SM.pdf}},
  year         = {{2016}},
}