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Problemy Upravleniya, 2017, Issue 4, Pages 26–36 (Mi pu1037)  

This article is cited in 1 scientific paper (total in 1 paper)

Control in the socio-economic systems

Nonparametric estimation of volatility and its parametric analogues

A. V. Dobrovidov, V. E. Tevosian

V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow
References:
Abstract: The article presents a method of non-parametric estimation of stochastic volatility and its comparison with other widely used algorithms in econometrics. The main advantage of this approach is the possibility to estimate the volatility in the case when its probability distribution is completely unknown. It is shown that the developed method has better characteristics in comparison with the known parametric algorithms, constructed on the basis of the GARCH model and the Kalman filter.
Keywords: stochastic volatility, nonparametric signal estimations, Kalman filter, GARCH, Taylor model.
Document Type: Article
UDC: 51-77+330.4
Language: Russian
Citation: A. V. Dobrovidov, V. E. Tevosian, “Nonparametric estimation of volatility and its parametric analogues”, Probl. Upr., 2017, no. 4, 26–36
Citation in format AMSBIB
\Bibitem{DobTev17}
\by A.~V.~Dobrovidov, V.~E.~Tevosian
\paper Nonparametric estimation of volatility and its parametric analogues
\jour Probl. Upr.
\yr 2017
\issue 4
\pages 26--36
\mathnet{http://mi.mathnet.ru/pu1037}
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  • https://www.mathnet.ru/eng/pu1037
  • https://www.mathnet.ru/eng/pu/v4/p26
  • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
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