We study the association of startup firm spending with firm survival. We propose that spending per employee (the “normalized burn rate”) captures entrepreneur's ability to avoid failure better than total spending (the popular “burn rate”). We derive an analytical model to describe how...

We investigate the accuracy of capital investment predictors from a national business survey of South African manufacturing. Based on data available to correspondents at the time of survey completion, we propose variables that might inform the confidence that can be attached to their...

SEC rules require managers to reconcile their non-GAAP forecasts with the most directly comparable GAAP measure unless doing so would entail ‘unreasonable effort'. A significant and growing number of managers invoke the unreasonable efforts exception to justify the omission of comparable GAAP...

We analyze tournaments of heterogeneous players from an organizer's perspective. Using a simple model of a noisy tournament, we demonstrate how the likelihood of selecting the best player, here termed the "predictive power" of a tournament, depends on the tournament format, the distribution of...

We set out in this study to review a vast amount of recent literature on machine learning (ML) approaches to predicting financial distress (FD), including supervised, unsupervised and hybrid supervised-unsupervised learning algorithms. Four supervised ML models including the traditional support...

We conduct laboratory experiments on variants of market scoring rule prediction markets, under different information distribution patterns, in order to evaluate the efficiency and speed of information aggregation, as well as test recent theoretical results on manipulative behavior by traders. We...