BibTex Citation Data :
@article{J.Gauss14772, author = {Noveda Wibowo and Sugito Sugito and Agus Rusgiyono}, title = {PEMODELAN RETURN SAHAM PERBANKAN MENGGUNAKAN EXPONENTIAL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (EGARCH)}, journal = {Jurnal Gaussian}, volume = {6}, number = {1}, year = {2017}, keywords = {eturn, Heteroscedasticity, Asymmetric effect, ARCH/GARCH, EGARCH.}, abstract = { ARIMA model is basically one of the models that can be applied in the time series data. In this ARIMA model, there is an assumption that the error variance of this model is constant. The price of stocks of the time series financial data, especially return has the trend to change quickly from time to time and it is actually fluctuative , so its error variance is inconstant or in another word, it calls as heteroscedasticity. To overcome this problem, it can be used the model of Autoregressive Conditional Heteroscedasticity (ARCH) or Generalized Autoregressive Conditional Heteroscedasticiy (GARCH). Furthermore, the financial data commonly has the different effect between the value of positive error and negative error toward the volatility data that is known as asymmetric effect. Indeed, one of the models used in this research, to overcome the problem of either heteroscedasticity or asymmetric effect toward the return of the close-stocks price of Banking daily is GARCH of asymmetric model that is Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH). The data of this research is the return data of the close-stocks price of Banking in November 1 st 2013 to August 24 th 2016. From the result of this analysis, it is gained several models of EGARCH. ARIMA model ([2,4],0,[2,4])-EGARCH (1,1) is such a best model for it has the lowest AIC value than any other models. Keywords : Return, Heteroscedasticity, Asymmetric effect, ARCH/GARCH, EGARCH. }, issn = {2339-2541}, pages = {91--99} doi = {10.14710/j.gauss.6.1.91-99}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/14772} }
Refworks Citation Data :
ARIMA model is basically one of the models that can be applied in the time series data. In this ARIMA model, there is an assumption that the error variance of this model is constant. The price of stocks of the time series financial data, especially return has the trend to change quickly from time to time and it is actually fluctuative, so its error variance is inconstant or in another word, it calls as heteroscedasticity. To overcome this problem, it can be used the model of Autoregressive Conditional Heteroscedasticity (ARCH) or Generalized Autoregressive Conditional Heteroscedasticiy (GARCH). Furthermore, the financial data commonly has the different effect between the value of positive error and negative error toward the volatility data that is known as asymmetric effect. Indeed, one of the models used in this research, to overcome the problem of either heteroscedasticity or asymmetric effect toward the return of the close-stocks price of Banking daily is GARCH of asymmetric model that is Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH). The data of this research is the return data of the close-stocks price of Banking in November 1st 2013 to August 24th 2016. From the result of this analysis, it is gained several models of EGARCH. ARIMA model ([2,4],0,[2,4])-EGARCH (1,1) is such a best model for it has the lowest AIC value than any other models.
Keywords: Return, Heteroscedasticity, Asymmetric effect, ARCH/GARCH, EGARCH.
Article Metrics:
Last update:
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to Media Statistika journal and Department of Statistics, Universitas Diponegoro as the publisher of the journal. Copyright encompasses the rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms, and any other similar reproductions, as well as translations.
Jurnal Gaussian and Department of Statistics, Universitas Diponegoro and the Editors make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in Jurnal Gaussian journal are the sole and exclusive responsibility of their respective authors and advertisers.
The Copyright Transfer Form can be downloaded here: [Copyright Transfer Form Jurnal Gaussian]. The copyright form should be signed originally and send to the Editorial Office in the form of original mail, scanned document or fax :
Dr. Rukun Santoso (Editor-in-Chief) Editorial Office of Jurnal GaussianDepartment of Statistics, Universitas DiponegoroJl. Prof. Soedarto, Kampus Undip Tembalang, Semarang, Central Java, Indonesia 50275Telp./Fax: +62-24-7474754Email: jurnalgaussian@gmail.com
Jurnal Gaussian by Departemen Statistika Undip is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Visitor Number:
View statistics
