PEMODELAN DATA TIME SERIES ASIMETRIK DENGAN EXPONENTIAL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (EGARCH)
| Main Author: | Binsar Hermawan, 1517031175 |
|---|---|
| Format: | Bachelors NonPeerReviewed Book Report |
| Terbitan: |
FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM
, 2019
|
| Subjects: | |
| Online Access: |
http://digilib.unila.ac.id/55822/1/1.%20ABSTRAK.pdf http://digilib.unila.ac.id/55822/2/2.%20SKRIPSI%20FULL.pdf http://digilib.unila.ac.id/55822/3/3.%20SKRIPSI%20FULL%20TANPA%20BAB%20PEMBAHASAN.pdf http://digilib.unila.ac.id/55822/ |
Daftar Isi:
- ABSTRACT ASIMETRIC TIME SERIES DATA MODELING WITH EXPONENTIAL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (EGARCH) By Binsar Hermawan In the case of financial data, it usually tends to fluctuate rapidly from time to time so that the variance of the error will always change every time (heterogeneous) but also has an asymmetrical effect. The purpose of this study is to apply the best EGARCH model on closing price return data of PT Jasa Marga Tbk. which has asymmetric in its volatility. The results of this study found that the best model is EGARCH (1.3) with the following equation: ln