Author Contribution - DFAS & AFMF

Fuente: Zenodo
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Dettagli Bibliografici
Autore principale: Alaali, Hasan mohamed
Natura: Recurso digital
Pubblicazione: Zenodo 2025
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author Alaali, Hasan mohamed
Alaali, Hasan mohamed
author_facet Alaali, Hasan mohamed
Alaali, Hasan mohamed
contents <p>This document formally records the authorship roles, intellectual functions, and strategic contributions of Hasan Mohamed Husain Alaali in the development of the Dynamic Financial Applied Science (DFAS) discipline and the Alaali Financial Models Framework (AFMF). It outlines the founding logic, simulation architecture, machine learning integration, model governance, and doctrinal innovations authored by Alaali across over 170 financial models. The document also highlights first-in-field contributions, including the Monte Carlo–driven Threshold Discovery Simulation (TDS) Engine and the ML-validated A-CFVI-ESG-X model. It is intended to serve as a permanent record of authorship integrity, intellectual structure, and innovation leadership.</p> <p> </p> <p>DFAS, AFMF, authorship contribution, financial modeling, Monte Carlo simulation, machine learning validation, A-ICR, A-CFVI, TDS Engine, MLIF, model governance, financial simulation, ESG risk, IP protection, financial science</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_15686167
institution Zenodo
language
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Author Contribution - DFAS & AFMF
Alaali, Hasan mohamed
Alaali, Hasan mohamed
DFAS
AFMF
authorship contribution
financial modeling
monte carlo simulation
machine learning validation
A-ICR
A-CFVI
TDS Engine
MLIF
Model Governance
financial simulation
ESG risk
IP protection
financial science
<p>This document formally records the authorship roles, intellectual functions, and strategic contributions of Hasan Mohamed Husain Alaali in the development of the Dynamic Financial Applied Science (DFAS) discipline and the Alaali Financial Models Framework (AFMF). It outlines the founding logic, simulation architecture, machine learning integration, model governance, and doctrinal innovations authored by Alaali across over 170 financial models. The document also highlights first-in-field contributions, including the Monte Carlo–driven Threshold Discovery Simulation (TDS) Engine and the ML-validated A-CFVI-ESG-X model. It is intended to serve as a permanent record of authorship integrity, intellectual structure, and innovation leadership.</p> <p> </p> <p>DFAS, AFMF, authorship contribution, financial modeling, Monte Carlo simulation, machine learning validation, A-ICR, A-CFVI, TDS Engine, MLIF, model governance, financial simulation, ESG risk, IP protection, financial science</p>
title Author Contribution - DFAS & AFMF
topic DFAS
AFMF
authorship contribution
financial modeling
monte carlo simulation
machine learning validation
A-ICR
A-CFVI
TDS Engine
MLIF
Model Governance
financial simulation
ESG risk
IP protection
financial science
url https://doi.org/10.5281/zenodo.15686167