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.
Acknowledgements
The authors would like to thank the Editor-in-Chief and anonymous referees for their insightful suggestions, comments and careful reading of the manuscript.
References
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Articles in the same Issue
- Frontmatter
- The 𝑛𝑝-Chart with 3-𝜎 Limits and the ARL-Unbiased 𝑛𝑝-Chart Revisited
- General Independent Competing Risks for Maintenance Analysis
- On Normal-Laplace Stochastic Volatility Model
- Robust Optimization of an Imperfect Process when the Mean and Variance are Jointly Monitored under Dependent Multiple Assignable Causes
- Estimation and Confidence Intervals of Modified Process Capability Index Using Robust Measure of Variability
- Cumulative Entropy and Income Analysis
Articles in the same Issue
- Frontmatter
- The 𝑛𝑝-Chart with 3-𝜎 Limits and the ARL-Unbiased 𝑛𝑝-Chart Revisited
- General Independent Competing Risks for Maintenance Analysis
- On Normal-Laplace Stochastic Volatility Model
- Robust Optimization of an Imperfect Process when the Mean and Variance are Jointly Monitored under Dependent Multiple Assignable Causes
- Estimation and Confidence Intervals of Modified Process Capability Index Using Robust Measure of Variability
- Cumulative Entropy and Income Analysis