PEMODELAN DATA TIME SERIES ASIMETRIK DENGAN EXPONENTIAL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (EGARCH)

Binsar Hermawan, 1517031175 (2019) PEMODELAN DATA TIME SERIES ASIMETRIK DENGAN EXPONENTIAL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (EGARCH). FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM, UNIVERSITAS LAMPUNG.

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Abstrak (Berisi Bastraknya saja, Judul dan Nama Tidak Boleh di Masukan)

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

Jenis Karya Akhir:	Skripsi
Subyek:	> QA Mathematics
Program Studi:	FAKULTAS MIPA > Prodi Matematika
Pengguna Deposit:	AM.d Firlia Hidayah
Date Deposited:	11 Mar 2022 07:59
Terakhir diubah:	11 Mar 2022 07:59
URI:	http://digilib.unila.ac.id/id/eprint/54389

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