Dynamic forecasts of financial distress have received far less attention than static forecasts, particularly in Australia. This study, therefore, investigates dynamic probability forecasts for Australian firms. Novel features of the modelling are the use of time-varying variables in forecasts from a Cox model. Not only is this one of relatively few studies to apply dynamic variables in forecasting financial distress, but to the authors' knowledge it is the first to provide forecasts of survival probabilities using the Cox model with time-varying variables. Forecast accuracy is evaluated using receiver operating characteristics curves and the Brier Score. It was found that the dynamic model had superior predictive power, in out-of-sample forecasts, to the traditional Cox model and to the logit model.
Graham PartingtonBusiness School, The University of Sydney, Australia
AbstractDynamic forecasts of financial distress have received far less attention than static forecasts, particularly in Australia. This study, therefore, investigates dynamic probability forecasts for Australian firms. Novel features of the modelling are the use of time-varying variables in forecasts from a Cox model. Not only is this one of relatively few studies to apply dynamic variables in forecasting financial distress, but to the authors' knowledge it is the first to provide forecasts of survival probabilities using the Cox model with time-varying variables. Forecast accuracy is evaluated using receiver operating characteristics curves and the Brier Score. It was found that the dynamic model had superior predictive power, in out-of-sample forecasts, to the traditional Cox model and to the logit model.