Robust recursive estimation of GARCH models

Tomáš Cipra; Radek Hendrych

Kybernetika (2018)

  • Volume: 54, Issue: 6, page 1138-1155
  • ISSN: 0023-5954

Abstract

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The robust recursive algorithm for the parameter estimation and the volatility prediction in GARCH models is suggested. It seems to be useful for various financial time series, in particular for (high-frequency) log returns contaminated by additive outliers. The proposed procedure can be effective in the risk control and regulation when the prediction of volatility is the main concern since it is capable to distinguish and correct outlaid bursts of volatility. This conclusion is demonstrated by simulations and real data examples presented in the paper.

How to cite

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Cipra, Tomáš, and Hendrych, Radek. "Robust recursive estimation of GARCH models." Kybernetika 54.6 (2018): 1138-1155. <http://eudml.org/doc/294821>.

@article{Cipra2018,
abstract = {The robust recursive algorithm for the parameter estimation and the volatility prediction in GARCH models is suggested. It seems to be useful for various financial time series, in particular for (high-frequency) log returns contaminated by additive outliers. The proposed procedure can be effective in the risk control and regulation when the prediction of volatility is the main concern since it is capable to distinguish and correct outlaid bursts of volatility. This conclusion is demonstrated by simulations and real data examples presented in the paper.},
author = {Cipra, Tomáš, Hendrych, Radek},
journal = {Kybernetika},
keywords = {GARCH model; Kalman filter; outlier; robust recursive estimation; volatility},
language = {eng},
number = {6},
pages = {1138-1155},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Robust recursive estimation of GARCH models},
url = {http://eudml.org/doc/294821},
volume = {54},
year = {2018},
}

TY - JOUR
AU - Cipra, Tomáš
AU - Hendrych, Radek
TI - Robust recursive estimation of GARCH models
JO - Kybernetika
PY - 2018
PB - Institute of Information Theory and Automation AS CR
VL - 54
IS - 6
SP - 1138
EP - 1155
AB - The robust recursive algorithm for the parameter estimation and the volatility prediction in GARCH models is suggested. It seems to be useful for various financial time series, in particular for (high-frequency) log returns contaminated by additive outliers. The proposed procedure can be effective in the risk control and regulation when the prediction of volatility is the main concern since it is capable to distinguish and correct outlaid bursts of volatility. This conclusion is demonstrated by simulations and real data examples presented in the paper.
LA - eng
KW - GARCH model; Kalman filter; outlier; robust recursive estimation; volatility
UR - http://eudml.org/doc/294821
ER -

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