Melola Discovery

← Melola Discovery

Open access Jurnal SINTA 3

STRENGTHENING SYARIAH FINANCIAL MARKETS WITH GARCH-BASED STOCK PRICE FORECASTING AND VAR-RISK ASSESSMENT

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 19 No. 2 (2025) · pp. 1217–1236

DOI
10.30598/barekengvol19iss2pp1217-1236
ISSN
2615-3017, 1978-7227
Published
2025-04-01
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Indonesia, as the largest Muslim-majority country, has significant potential to enhance its Shariah financial sector, which has been growing rapidly, around 7.43% from 2023 to 2024, and contributing to the national economy. However, political and natural disasters have influenced the economy and Shariah-compliant stocks. This study focuses on forecasting Shariah-compliant stock prices using Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models and estimating investment risks via Value at Risk (VaR) for four Islamic banks listed in IDX: BRIS, BTPS, BANK, and PNBS. The findings indicate that GARCH models effectively capture stock price dynamics and provide accurate 10-day forecasts. Additionally, the models reliably predict VaR, validated through backtesting at various confidence levels. These insights are valuable for financial regulators and risk managers, aiding in policy design to ensure market stability by enabling the implementation of measures such as stricter capital reserve requirements for institutions with high-risk exposure and mandatory adoption of advanced risk management techniques like dynamic stress testing. Such policies not only mitigate systemic risks during periods of financial volatility but also enhance the overall resilience and robustness of the financial system. For investors, accurate risk predictions support informed decision-making, enhance portfolio protection, and optimize risk management.

Collaboration network of the authors

40 authors · 88 co-authorship links · 17 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • University of Brawijaya
  • Universitas Widya Kartika
  • Institut Agama Islam Negeri Kendari
  • Universitas Halu Oleo
  • Universitas Muhammadiyah Parepare
  • State University of Semarang
  • Universitas Kartini
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Nur Silviyah RahmiAffiliation unknown4
Solimun SolimunUniversity of Brawijaya4
Jopang JopangUniversitas Halu Oleo3
Akhyar AbdullahUniversitas Halu Oleo3
Adji Achmad Rinaldo FernandesUniversity of Brawijaya3
Makmur KambolongUniversitas Halu Oleo2
Mustakim MustakimUniversitas Muhammadiyah Parepare2
Erni QomariyahAffiliation unknown2
Ani Budi AstutiUniversity of Brawijaya2
Henny PramoedyoUniversity of Brawijaya2
Agus SuryantoState University of Semarang2
Yulius HariUniversitas Widya Kartika1
Budi HermawanUniversitas Widya Kartika1
Endang SetyawatiUniversitas Kartini1
Indra Budi TrisnoUniversitas Widya Kartika1
Dimas Febrian ElviantoUniversitas Widya Kartika1
Alya Fitri SyalsabillaAffiliation unknown1
Alya Fitri SyalsabillaUniversity of Brawijaya1
Agus Fachrur RozyUniversity of Brawijaya1
Agus SusiloAffiliation unknown1
Galuh Wilujeng PuspaAffiliation unknown1
Miftakhul CahyatiAffiliation unknown1
Dodyk PranowoAffiliation unknown1
Sumardona SumardonaInstitut Agama Islam Negeri Kendari1
Sarlinda SarlindaInstitut Agama Islam Negeri Kendari1
Epiyana EpiyanaInstitut Agama Islam Negeri Kendari1
Sarnianti SarniantiInstitut Agama Islam Negeri Kendari1
Kamrin KamrinUniversitas Halu Oleo1
Ruslan MajidUniversitas Halu Oleo1
Megasari SidulaAffiliation unknown1
Nuryani NuryaniNational Research and Innovation Agency1
Muflih AzizAffiliation unknown1
Nooraini AsrudinAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc)
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">STRENGTHENING SYARIAH FINANCIAL MARKETS WITH GARCH-BASED STOCK PRICE FORECASTING AND VAR-RISK ASSESSMENT</dc:title>
	<dc:creator>Darmanto, Darmanto</dc:creator>
	<dc:creator>Darti, Isnani</dc:creator>
	<dc:creator>Astutik, Suci</dc:creator>
	<dc:creator>Nurjannah, Nurjannah</dc:creator>
	<dc:creator>Lee, Muhammad Hisyam</dc:creator>
	<dc:creator>Damayanti, Rismania Hartanti Putri Yulianing</dc:creator>
	<dc:creator>Irsandy, Diego</dc:creator>
	<dc:description xml:lang="en-US">Indonesia, as the largest Muslim-majority country, has significant potential to enhance its Shariah financial sector, which has been growing rapidly, around 7.43% from 2023 to 2024, and contributing to the national economy. However, political and natural disasters have influenced the economy and Shariah-compliant stocks. This study focuses on forecasting Shariah-compliant stock prices using Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models and estimating investment risks via Value at Risk (VaR) for four Islamic banks listed in IDX: BRIS, BTPS, BANK, and PNBS. The findings indicate that GARCH models effectively capture stock price dynamics and provide accurate 10-day forecasts. Additionally, the models reliably predict VaR, validated through backtesting at various confidence levels. These insights are valuable for financial regulators and risk managers, aiding in policy design to ensure market stability by enabling the implementation of measures such as stricter capital reserve requirements for institutions with high-risk exposure and mandatory adoption of advanced risk management techniques like dynamic stress testing. Such policies not only mitigate systemic risks during periods of financial volatility but also enhance the overall resilience and robustness of the financial system. For investors, accurate risk predictions support informed decision-making, enhance portfolio protection, and optimize risk management.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2025-04-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15543</dc:identifier>
	<dc:identifier>10.30598/barekengvol19iss2pp1217-1236</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application; 1217-1236</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol19iss2year2025</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15543/9969</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2025 Darmanto Darmanto, Isnani Darti, Suci Astutik, Nurjannah Nurjannah, Muhammad Hisyam Lee, Rismania Hartanti Putri Yulianing Damayanti, Diego Irsandy</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>