On Normal-Laplace Stochastic Volatility Model
Abstract This paper analyses a stochastic volatility model generated by first order normal-Laplace autoregressive process. The model parameters are estimated by the generalized method of moments. A simulation experiment is carried out to check the performance of the estimates. Finally, a real data analysis is provided to illustrate the practical utility of the proposed model and show that it captures the stylized factors of the financial return series.
Year of publication: |
2022
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Authors: | Kavungal, Shiji ; Thekkedath, Rahul |
Published in: |
Stochastics and Quality Control. - De Gruyter, ISSN 2367-2404, ZDB-ID 2905267-1. - Vol. 37.2022, 2, p. 127-136
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Publisher: |
De Gruyter |
Subject: | Stochastic Volatility | Normal-Laplace Distribution | Autoregressive Process | Generalized Method of Moments | Financial Time Series |
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