Markov-switching and noise-to-signal ratio approach for early detection of currency crises

International Journal of Advances in Applied Sciences 2026 Open access

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Authors: Sugiyanto Sugiyanto, Muhammad Bayu Nirwana, Isnandar Slamet, Etik Zukhronah, Syifa’ Salsabila Gita Parahita
DOI: 10.11591/ijaas.v15.i1.pp42-54
Cited by: 0
References: 44

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.

Fields of Study & Subjects

Global Financial Crisis and Policies Monetary Policy and Economic Impact Financial Risk and Volatility Modeling

Publication details

Journal / source
International Journal of Advances in Applied Sciences
Volume
15
Issue
1
Pages
42–42
Publication date
1 March 2026
Language
EN