This paper aims to extend the research into company financial forecasts by modelling naïve earnings forecasts derived from normalised historic accounting data disclosed during Australian initial public offerings (IPOs). It seeks to investigate naïve forecast errors and compare them against their management forecast counterparts. It also seeks to investigate determinants of differential error behaviour.
IPOs were sampled and their prospectus forecasts, historic financial data and subsequent actual financial performance were analysed. Directional and absolute forecast error behaviour was analysed using univariate and multivariate techniques.
Systematic factors associated with error behaviour were observed across the management forecasts and the naïve forecasts, the most notable being audit quality. In certain circumstances, the naïve forecasts performed at least as well as management forecasts. In particular, forecast interval was an important discriminator for accuracy, with the superiority of management forecasts only observed for shorter forecast intervals.
The results imply a level of “disclosure management” regarding company IPO forecasts and normalised historic accounting data, with forecast overestimation and error size more extreme in the absence of higher quality third‐party monitoring services via the audit process. The results also raise questions regarding the serviceability of normalised historic financial information disclosed in prospectuses, in that many of those data do not appear to enhance the forecasting process, particularly when accompanied by published management forecasts and shorter forecast intervals.
