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All Journal International Journal of Computing Science and Applied Mathematics
Aprilia, Nabila Churin
Universitas Sebelas Maret
Computer Science & IT Education Mathematics

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Combined Model of Markov Switching and Asymmetry of Generalized Seasonal Autoregressive Moving Average Conditional Heteroscedasticity for Early Detection of Financial Crisis in Hong Kong Sugiyanto, Sugiyanto; Subanti, Sri; Slamet, Isnandar; Zukhronah, Etik; Susanto, Irwan; Sulandari, Winita; Aprilia, Nabila Churin
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 10, No 2 (2024)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.v10i2.21943

Abstract

The financial crisis in Hong Kong occurred in 1997 and 2008. To prevent a crisis or reduce the impact of a crisis, action is needed through early detection of the crisis using export indicator. The combination of Markov Switching and Asymmetric Generalized Seasonal Autoregressive Moving Average Conditional Heteroscedasticity (MS-AGSARMACH) models explains the crisis well. The results show that the MSAGSARMACH(2,1,1) model can explain past and future crises well.
Co-Authors Irwan Susanto Isnandar Slamet, Isnandar Sri Subanti Sugiyanto, Sugiyanto Sulandari, Winita Zukhronah, Etik