Agboluaje, Ayodele Abraham and Ismail, Suzilah Bt and Yip, Chee Yin (2024) Comparative Study of Estimation of the Asymmetric in Conditional Variance Using EGARCH Models and CWN Model. In: Mathematics and Computer Science: Contemporary Developments Vol. 7. BP International, pp. 170-183. ISBN 978-93-48119-70-4
Full text not available from this repository.Abstract
The aim of the study is to compare the asymmetry in the conditional variance of Exponential Generalized Autoregression Conditional Heteroscdastiicity (EGARCH) with the Combine White Noise (CWN) model to acquire reliable results. The EGARCH has high information criteria and low log likelihood while CWN has minimum information criteria and high log likelihood which makes CWN a more suitable estimation. CWN estimation is more efficient than EGARCH estimation when employing the determinant covariance matrix values. Minimum forecast error in CWN revealed better forecast accuracy when compared with EGARCH. Therefore, CWN estimation results have revealed more efficiency than the EGARCH model estimation in the overall results.
| Item Type: | Book Section |
|---|---|
| Subjects: | GO for ARCHIVE > Mathematical Science |
| Depositing User: | Unnamed user with email support@goforarchive.com |
| Date Deposited: | 19 Nov 2024 13:14 |
| Last Modified: | 19 Nov 2024 13:14 |
| URI: | http://eprints.go4mailburst.com/id/eprint/2449 |
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