This article is cited 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

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.

UDC: 51-77+330.4