AI/ML Simulation Validation of the Alaali Cash Flow Volatility Index (A-CFVI Core)

This document provides empirical validation for the Alaali Cash Flow Volatility Index (A-CFVI Core) through advanced artificial intelligence and machine learning techniques. Specifically, a Random Forest Regression model is employed using Cash Flow from Operations (CFO) data for Aluminum Bahrain (Alba) and Alcoa USA, covering the period from 2019 to 2023. The evaluation demonstrates the predictive accuracy and reliability of the A-CFVI Core metric through performance metrics such as Mean Absolute Error (MAE) and R-squared (R²), supporting its practical use in strategic financial modeling and risk assessment (Alaali, 2025).