Usman, Mustofa and indryani, N and Warsono, Warsono and Amanto, Amanto and Wamiliana, Wamiliana (2020) DYNAMIC MODELING OF TIME SERIES DATA USING BEKK-GARCH MODEL. Periodico Tche Quimica, 17 (36). ISSN 2179-0302

Periodico36 [makalah ke-86] (2).pdf

Download (5MB) | Preview


The Vector Autoregressive Moving Average (VARMA) model is one of the models that is often used in modeling multivariate time series data. In time series data of economic, especially data return, usually they have high fluctuations in some periods of time, so that the volatility of the return is unstable. In the process of modeling data return of share prices ADRO and ITMG, the behavior of high volatility will be considered. The aims of this study are to find the best model that fit to the data return of share price of the energy companies of PT Adaro Energy Tbk (ADRO) and PT Indo Tambangraya Megah Tbk (ITMG), to analyze the behavior of impulse response of the variables data return ADRO and ITMG, to analyze the granger causality test, and to forecast the next 12 periods. Based on the selection of the best model using the criteria of AICC, HQC, AIC and SBC, it was found that the VARMA (2.2) -GARCH (1.1) model is the best one for the data in this study. Based on the best model selected the impulse response, granger causality test, and forecasting for the next 12 periods are discussed.

Item Type: Article
Subjects: Q Science > QA Mathematics
Divisions: Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Prodi Matematika
Depositing User: WAMILIANA
Date Deposited: 18 May 2021 03:57
Last Modified: 18 May 2021 03:57

Actions (login required)

View Item View Item