Usman, Mustofa and Ambarwati, Riyama and Barusman, M Yusuf S and Elfaki, Faiz A. M. and Widiarti, Widiarti (2018) Modeling and Forecasting Time Series Data By EGARCH Model. Journal of Engineering and Applied Sciences, 13 (9). pp. 2593-2602. ISSN 1818-7803 (Online)

[img] Text
Medwell Journals_2018 Mustofa_Riyama_Widiarti.pdf

Download (964kB)
[img] Text
index.html_doi=jeasci.2018.2593.2602

Download (18kB)
Official URL: https://medwelljournals.com/journalhome.php?jid=18...

Abstract

In analysis of time series data, the class of GARCH Models in many studies has proved very valuable in modeling time series with time varying volatility, especially in financial time series data. The behavior of financial data sometimes are not only have a high volatility and heterogeneous variances but also have an asymmetric effect or leverage effect due to the price down (bad news) and the price increase (good news). One of the models that can cope with the asymmetric effect is Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) Model. The aims of this study is to find the best EGARCH Model for forecasting data share of PT. Tambang Batu Bara Bukit Asam Tbk from January 2009-February 2016. The results shown that the best model are ARIMA (1, 1, 0) Model and EGARCH (1.1) Models. The forecasting results also sound good and within the 95% confidence interval.

Item Type: Article
Subjects: Q Science > QA Mathematics
Divisions: Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Prodi Matematika
Depositing User: WIDIARTI
Date Deposited: 06 Sep 2018 07:59
Last Modified: 06 Sep 2018 07:59
URI: http://repository.lppm.unila.ac.id/id/eprint/8735

Actions (login required)

View Item View Item