Nonparametric Estimation of Volatility and Its Parametric Analogs
- 作者: Dobrovidov A.V.1, Tevosian V.E.1
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隶属关系:
- Trapeznikov Institute of Control Sciences
- 期: 卷 79, 编号 9 (2018)
- 页面: 1687-1702
- 栏目: Control Sciences
- URL: https://journals.rcsi.science/0005-1179/article/view/151022
- DOI: https://doi.org/10.1134/S0005117918090126
- ID: 151022
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详细
This paper suggests a nonparametric method for stochastic volatility estimation and its comparison with other widespread econometric algorithms. A major advantage of this approach is that the volatility can be estimated even in the case of its completely unknown probability distribution. As demonstrated below, the new method has better characteristics against the popular parametric algorithms based on the GARCH model and Kalman filter.
作者简介
A. Dobrovidov
Trapeznikov Institute of Control Sciences
编辑信件的主要联系方式.
Email: dobrovidov@gmail.com
俄罗斯联邦, Moscow
V. Tevosian
Trapeznikov Institute of Control Sciences
Email: dobrovidov@gmail.com
俄罗斯联邦, Moscow
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