When Profits Do Not Ensure Future Stability: A Structural Early-Warning Framework

This paper introduces the Deep Activity Structural Framework (DASF), a structural regime model designed to diagnose enterprise financial deterioration prior to observable distress. Unlike traditional default prediction models that rely on static financial ratios or probability scores, DASF formalizes viability as a dynamic condition derived from the coherence between economic activity and internally generated operating cash flow. The framework introduces Coherent Temporal Conversion (CTC), its intertemporal slope, and structural closure conditions to identify regime migration from sustainable to dependent states. Monte Carlo stress simulations indicate a consistent lead-time advantage relative to static baseline models, particularly under crisis conditions, capex-intensive structures, and earnings management environments. A comprehensive empirical validation blueprint is provided to guide real-world testing under journal-level standards, including explicit hypotheses, variable construction rules, comparator models, robustness protocols, and falsification procedures. DASF is positioned as a structural early-warning complement within financial stability research.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-12
DOI
https://doi.org/10.5281/zenodo.18627561
Primary Topic
Financial Distress and Bankruptcy Prediction
Type
article
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article

When Profits Do Not Ensure Future Stability: A Structural Early-Warning Framework

Jorge Bustos Vargas
Zenodo (CERN European Organization for Nuclear Research)
Financial Distress and Bankruptcy Prediction
article

When Profits Do Not Ensure Future Stability: A Structural Early-Warning Framework

Jorge Bustos Vargas
article en

Abstract

This paper introduces the Deep Activity Structural Framework (DASF), a structural regime model designed to diagnose enterprise financial deterioration prior to observable distress. Unlike traditional default prediction models that rely on static financial ratios or probability scores, DASF formalizes viability as a dynamic condition derived from the coherence between economic activity and internally generated operating cash flow. The framework introduces Coherent Temporal Conversion (CTC), its intertemporal slope, and structural closure conditions to identify regime migration from sustainable to dependent states. Monte Carlo stress simulations indicate a consistent lead-time advantage relative to static baseline models, particularly under crisis conditions, capex-intensive structures, and earnings management environments. A comprehensive empirical validation blueprint is provided to guide real-world testing under journal-level standards, including explicit hypotheses, variable construction rules, comparator models, robustness protocols, and falsification procedures. DASF is positioned as a structural early-warning complement within financial stability research.

Zenodo (CERN European Organization for Nuclear Research)
Reduced inequalities
Openalex Percentile: Top 57%
Financial Distress and Bankruptcy Prediction
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When Profits Do Not Ensure Future Stability: A Structural Early-Warning Framework — Jorge Bustos Vargas · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS