A heuristic framework for ratio-based modelling of corporate collapse

This paper draws on empirical evidence to demonstrate that a heuristic framework signals collapse with significantly higher accuracy than the traditional static approach. Using a sample of 494 US publicly listed companies comprising 247 collapsed matched with 247 financially healthy ones, a heuristic framework is decisively superior the closer one gets to the event of collapse, culminating in 12.5% more overall accuracy than a static approach during
the year of collapse. An even more dramatic improvement occurs in relation to reduction of Type I error, with a heuristic framework delivering an improvement of 66.7% over its static counterpart.