Detecting and explaining bubbles in Islamic stock markets: A dual approach with LPPLS and machine learning

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dc.contributor.authorSaritas, Merve Mert
dc.contributor.authorÖzgür, Önder
dc.contributor.authorYilanci, Veli
dc.date.accessioned2026-02-03T11:53:48Z
dc.date.available2026-02-03T11:53:48Z
dc.date.issued2026
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractThis study investigates the presence and predictability of price bubbles in Islamic stock markets, challenging the proposition that their Sharia-compliant principles provide inherent resilience against such phenomena. Employing a dual methodology, we first apply the Log-Periodic Power Law Singularity (LPPLS) model to detect crash periods in the daily Dow Jones Islamic Market indices for Canada, Japan, the United Kingdom, and the United States from 1996 to 2025. Subsequently, we utilize an eXtreme Gradient Boosting (XGBoost) algorithm to identify the key macro-financial drivers of these identified bubble episodes. The results from the LPPLS analysis confirm that these indices exhibit significant bubble dynamics. The XGBoost model incorporated imbalance-aware learners and further reveals that the probability of a bubble is systematically linked to a combination of market-based and macroeconomic variables, with the stock price index, intraday volatility, long-term interest rates, and exchange rates emerging as the most significant predictors, albeit with country-specific variations. © 2026 Borsa İstanbul Anonim Şirketi.
dc.identifier.doi10.1016/j.bir.2026.100790
dc.identifier.issn2214-8450
dc.identifier.scopus2-s2.0-105026688470
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.bir.2026.100790
dc.identifier.urihttps://hdl.handle.net/20.500.12428/34305
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherBorsa Istanbul Anonim Sirketi
dc.relation.ispartofBorsa Istanbul Review
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_Scopus_20260130
dc.subjectIslamic stock markets
dc.subjectMachine learning
dc.subjectSpeculative bubbles
dc.titleDetecting and explaining bubbles in Islamic stock markets: A dual approach with LPPLS and machine learning
dc.typeArticle

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