Scenario-based portfolio optimization via bootstrapping and machine learning methods: Theory development and empirical evidence from the Tehran Stock Market.
- DOI
- 10.1371/journal.pone.0342593
- Published
- 2026
- Container
- PloS one
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1371/journal.pone.0342593,
title = {Scenario-based portfolio optimization via bootstrapping and machine learning methods: Theory development and empirical evidence from the Tehran Stock Market.},
author = {Amini M and Javadi S and Soleimani-Damaneh M},
year = {2026},
journal = {PloS one},
doi = {10.1371/journal.pone.0342593},
url = {https://doi.org/10.1371/journal.pone.0342593}
}RIS
TY - JOUR TI - Scenario-based portfolio optimization via bootstrapping and machine learning methods: Theory development and empirical evidence from the Tehran Stock Market. AU - Amini M AU - Javadi S AU - Soleimani-Damaneh M PY - 2026 JO - PloS one DO - 10.1371/journal.pone.0342593 UR - https://doi.org/10.1371/journal.pone.0342593 ER -
APA
M, A., S, J., & M, S. (2026). Scenario-based portfolio optimization via bootstrapping and machine learning methods: Theory development and empirical evidence from the Tehran Stock Market.. PloS one. https://doi.org/10.1371/journal.pone.0342593
Source records
- pubmed · retrieved 2026-09-25T21:34:01.917Z