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Estimation of the parameters of symmetric stable ARMA and ARMA–GARCH modelsPublished in Taylor and Francis Ltd.
2021
In this article, we first propose the modified Hannan–Rissanen Method for estimating the parameters of autoregressive moving average (ARMA) process with symmetric stable noise and symmetric stable generalized autoregressive conditional heteroskedastic (GARCH) noise. Next, we propose the modified empirical characteristic function method for the estimation of GARCH parameters with symmetric stable noise. Further, we show the efficiency, accuracy and simplicity of our methods with Monte-Carlo simulation. Finally, we apply our proposed methods to model the financial data. © 2021 Informa UK Limited, trading as Taylor & Francis Group.
Topics: Noise (61)%61% related to the paper, Autoregressive–moving-average model (60)%60% related to the paper and Estimation theory (53)%53% related to the paper
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Postprint Version
Content may be subject to copyright.This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Applied Statistics on 2021-05-1... ...This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Applied Statistics on 2021-05-18, available online: https://www.tandfonline.com/10.1080/02664763.2021.1928019.
About the journal
| Journal | Data powered by TypesetJournal of Applied Statistics |
|---|---|
| Publisher | Data powered by TypesetTaylor and Francis Ltd. |
| ISSN | 02664763 |
| Open Access | No |
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