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

International Journal of Advances in Applied Sciences · Vol. 15 No. 1 (2026) · hlm. 42–54

DOI
10.11591/ijaas.v15.i1.pp42-54
ISSN
2722-2594, 2252-8814
Terbit
2026-03-01
Penerbit
Institute of Advanced Engineering and Science
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

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.

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40 penulis · 159 tautan kepenulisan bersama · 13 lintas organisasi · menampilkan 40 yang paling banyak terhubung

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  • Sebelas Maret University
  • State University of Semarang
  • Universitas Nahdlatul Ulama Blitar
  • Hasanuddin University
  • Diponegoro University
  • Afiliasi tidak diketahui
  • Organisasi berbeda
  • Organisasi sama
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Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Irwan SusantoSebelas Maret University2
Winita SulandariSebelas Maret University2
Isa AkhlisState University of Semarang2
Wahyu HardyantoAfiliasi tidak diketahui2
Langlang HandayaniAfiliasi tidak diketahui2
Sugianto SugiantoUniversitas Nahdlatul Ulama Blitar2
Budi AstutiAfiliasi tidak diketahui2
Ani RusilowatiState University of Semarang2
Agus KristiyantoAfiliasi tidak diketahui2
Sunyoto Eko NugrohoState University of Semarang2
Hasih PratiwiSebelas Maret University2
Titis Jati NugrahaSebelas Maret University1
İsnandar SlametSebelas Maret University1
Sri SubantiSebelas Maret University1
Sugianto SugiantoHasanuddin University1
Ida Ayu Preharsini KusumaAfiliasi tidak diketahui1
Esa Permata Sari Putri IlahiSebelas Maret University1
Fauzi Nafi'udinSebelas Maret University1
Respatiwulan RespatiwulanSebelas Maret University1
Yuliana SusantiSebelas Maret University1
Sri Sulistijowati HandajaniSebelas Maret University1
Lintang Pramesti NareswariSebelas Maret University1
Mutiara QalbuSebelas Maret University1
Siti WahyuniAfiliasi tidak diketahui1
Fianti FiantiAfiliasi tidak diketahui1
Husna ArifahAfiliasi tidak diketahui1
Delvananta GivarinAfiliasi tidak diketahui1
Putut MarwotoState University of Semarang1
Sutikno SutiknoDiponegoro University1
Ellianawati EllianawatiState University of Semarang1
Budi Naini MindiyartoAfiliasi tidak diketahui1
Agus YuliantoAfiliasi tidak diketahui1
Nur’ainiyyah HasniAfiliasi tidak diketahui1
Shelly Salista RahmayantiAfiliasi tidak diketahui1
Candra FanleonAfiliasi tidak diketahui1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) http://ijaas.iaescore.com/index.php/IJAAS/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Markov-switching and noise-to-signal ratio approach for early detection of currency crises</dc:title>
	<dc:creator>Sugiyanto, Sugiyanto</dc:creator>
	<dc:creator>Nirwana, Muhammad Bayu</dc:creator>
	<dc:creator>Slamet, Isnandar</dc:creator>
	<dc:creator>Zukhronah, Etik</dc:creator>
	<dc:creator>Parahita, Syifa’ Salsabila Gita</dc:creator>
	<dc:description xml:lang="en-US">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.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2026-03-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijaas.iaescore.com/index.php/IJAAS/article/view/22245</dc:identifier>
	<dc:identifier>10.11591/ijaas.v15.i1.pp42-54</dc:identifier>
	<dc:source xml:lang="en-US">International Journal of Advances in Applied Sciences; Vol 15, No 1: March 2026; 42-54</dc:source>
	<dc:source>2722-2594</dc:source>
	<dc:source>2252-8814</dc:source>
	<dc:source>10.11591/ijaas.v15.i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijaas.iaescore.com/index.php/IJAAS/article/view/22245/13428</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 Sugiyanto, Muhammad Bayu Nirwana, Isnandar Slamet, Etik Zukhronah, Syifa’ Salsabila Gita Parahita</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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