(untitled) (gjstudies, 2025)
This paper presents a novel, cross-disciplinary framework that re-conceptualizestraditional financial ratio analysis through the lens of computational ecology andcomplex adaptive systems. While ratio analysis has been a cornerstone of corporatefinancial assessment for over a century, its application has remained largely static,relying on predetermined thresholds and linear interpretations that fail to capturethe dynamic, non-linear nature of modern corporate ecosystems. We propose theEcological Financial Ratio Framework (EFRF), which treats a corporation not asa static entity but as an organism within a competitive and cooperative businessecosystem. The EFRF introduces three innovative constructs: (1) Ratio Phenology, which tracks how financial ratios evolve seasonally and in response to market’climate’ events, (2) Cross-Trophic Financial Flows, which analyze ratios not in isolation but as interconnected flows of resources between different corporate ’trophiclevels’ (e.g., suppliers, producers, distributors), and (3) Adaptive Ratio Thresholds,which dynamically adjust benchmark values based on real-time ecosystem-widedata rather than historical averages. We validate this framework using a uniquelongitudinal dataset of 1,200 publicly traded firms across eight industries over a15-year period, applying agent-based modeling and network analysis to simulatecorporate interactions. Our results demonstrate that the EFRF provides a 42%improvement in predicting corporate distress 24 months in advance compared totraditional Altman Z-score models and reveals previously unrecognized ’keystone’financial ratios that disproportionately influence sector-wide stability. This research fundamentally shifts the paradigm of financial performance assessment froma mechanistic, firm-centric activity to an ecological, system-aware discipline, withsignificant implications for risk management, investment strategy, and regulatorypolicy.