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All Journal International Journal of Advances in Applied Sciences
Parahita, Syifa’ Salsabila Gita
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Earth & Planetary Sciences Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Markov-switching and noise-to-signal ratio approach for early detection of currency crises Sugiyanto, Sugiyanto; Nirwana, Muhammad Bayu; Slamet, Isnandar; Zukhronah, Etik; Parahita, Syifa’ Salsabila Gita
International Journal of Advances in Applied Sciences Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i1.pp42-54

Abstract

Economic instability can easily lead to a currency crisis. Therefore, observing a number of crisis indicators is crucial for building an early warning system (EWS). However, selecting the indicators most responsive to the crisis is the best choice. For this purpose, the noise-to-signal ratio (NSR) method was used. Monthly data from 1990-1925 were used in the autoregressive moving average (ARMA), generalized autoregressive moving average with generalized autoregressive conditional heteroscedasticity (GARMACH), and Markov-switching (MS)-GARMACH hybrid models to explain the crisis. Model interpretation indicates that there will be no crisis from May 2025-April 2026.
Co-Authors Isnandar Slamet, Isnandar Nirwana, Muhammad Bayu Sugiyanto - Zukhronah, Etik