creators_name: Binsar Hermawan, 1517031175
creators_id: -
type: other
datestamp: 2022-03-11 07:59:45
lastmod: 2022-03-11 07:59:45
metadata_visibility: show
title: PEMODELAN DATA TIME SERIES ASIMETRIK DENGAN
EXPONENTIAL GENERALIZED AUTOREGRESSIVE CONDITIONAL
HETEROSCEDASTICITY (EGARCH)
ispublished: pub
subjects: QA
full_text_status: restricted
abstract: 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 
date: 2019-01-29
date_type: published
publisher: FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM
place_of_pub: UNIVERSITAS LAMPUNG
citation:   Binsar Hermawan, 1517031175  (2019) PEMODELAN DATA TIME SERIES ASIMETRIK DENGAN EXPONENTIAL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (EGARCH).  FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM, UNIVERSITAS LAMPUNG.     
document_url: http://digilib.unila.ac.id/54389/1/1.%20ABSTRAK.pdf
document_url: http://digilib.unila.ac.id/54389/2/2.%20SKRIPSI%20FULL.pdf
document_url: http://digilib.unila.ac.id/54389/3/3.%20SKRIPSI%20FULL%20TANPA%20BAB%20PEMBAHASAN.pdf