A Hybrid Model for Improving Malaysian Gold Forecast Accuracy
A hybrid model has been considered an effective way to improve forecast accuracy. This paper proposes the hybrid model of the linear autoregressive moving average (ARIMA) and the non-linear generalized autoregressive conditional heteroscedasticity (GARCH) in modeling and forecasting. Malaysian gold...
Main Authors: | Maizah Hura, Ahmad, Pung, Yean Ping, Siti Roslindar, Yaziz, Nor Hamizah, Miswan |
---|---|
Format: | Article |
Language: | English |
Published: |
Hikari Ltd
2014
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/7489/1/A_Hybrid_Model_for_Improving_Malaysian_Gold_Forecast_Accuracy.pdf |
Similar Items
-
Forecasting Malaysian Gold Using a Hybrid of ARIMA and GJR-GARCH Models
by: Siti Roslindar, Yaziz, et al.
Published: (2015) -
Forecasting Malaysian gold using a hybrid of ARIMA and GJR-GARCH models
by: Ahmad, Maizah Hura, et al.
Published: (2015) -
The performance of hybrid arima-garch modeling in forecasting gold price
by: Yaziz, Siti Roslindar, et al.
Published: (2013) -
Determination of sample size for higher volatile data using new framework of hybrid Box-Jenkins - GARCH: a case study on gold price
by: Siti Roslindar, Yaziz, et al.
Published: (2017) -
Innovations in the ARIMA - GARCH Modeling in Forecasting Gold Price
by: Siti Roslindar, Yaziz, et al.
Published: (2014)