Volatility Modeling Using ARCH/GARCH Method : Aplication on Asia Pasific Index
- https://doi.org/10.2991/isclo-15.2016.34How to use a DOI?
- Volatility, Index , ARIMA, ARCH/GARCH
The purpose of this study was to estimate the volatility model of Asia Pasific Index such as LQ45 (Indonesia), HSI (Hongkong), KLSE (Malaysia), STI (Singapore). The best ARIMA model for Asia Pasific Indexes are : LQ45 ( ARIMA (1,1,26)), HSI (ARIMA (14,1,14)), KLSE ( ARIMA (17,1,1)), and STI (ARIMA (17,1,11)). The heteroscedasticity test against the best ARIMA models, detected that the data is still contain heteroscedasticity. Then the determination of volatility obtained using Autoregressive Conditional Heteroscedasticity approach/ Generalized Autoregressive Conditional Heteroscedastic (ARCH / GARCH). The result indicate that the best GARCH model to determined the volatility of LQ45, STI, and HSI is GARCH (1.1) and KLSE is GARCH (3.0).
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Irni Yunita PY - 2016/03 DA - 2016/03 TI - Volatility Modeling Using ARCH/GARCH Method : Aplication on Asia Pasific Index BT - Proceedings of the 3rd International Seminar and Conference on Learning Organization (isclo-15) PB - Atlantis Press SP - 182 EP - 189 SN - 2352-5398 UR - https://doi.org/10.2991/isclo-15.2016.34 DO - https://doi.org/10.2991/isclo-15.2016.34 ID - Yunita2016/03 ER -