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Open Access

Peer-reviewed

Research Article

Scenario-based portfolio optimization via bootstrapping and machine learning methods: Theory development and empirical evidence from the Tehran Stock Market

Morteza Amini,

Roles Conceptualization, Formal analysis, Investigation, Methodology, Software, Validation, Writing – review & editing

Affiliation School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran, Tehran, Iran

https://orcid.org/0000-0003-4602-9653

⨯
Sajedeh Javadi,

Roles Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran, Tehran, Iran

https://orcid.org/0000-0002-2560-2206

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Majid Soleimani-damaneh

Roles Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Supervision, Validation, Writing – review & editing

* E-mail: m.soleimani.d@ut.ac.ir

Affiliation School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran, Tehran, Iran

https://orcid.org/0000-0002-5913-1035

⨯

Scenario-based portfolio optimization via bootstrapping and machine learning methods: Theory development and empirical evidence from the Tehran Stock Market

Morteza Amini,
Sajedeh Javadi,
Majid Soleimani-damaneh

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Published: February 19, 2026
https://doi.org/10.1371/journal.pone.0342593

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Stock markets
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Machine learning algorithms
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