Forecasting short run performance of initial public offerings in the Istanbul Stock Exchange

Previous research on IPOs has identified several factors or issue characteristics that play a role in the level of short term underpricing of initial public offerings. Some of those issue features are the firm size, market trend, size of the offer, investment banker reputation, method of intermediation, stock price range and investor type. The objective of this study is to develop a model based on these features to forecast the short term performance of IPOs in the Istanbul Stock Exchange. To this end we divided our sample period into a model building subperiod and a testing subperiod. After identifying 9 issue features that are related to IPO short term pricing, we estimated our models using multiple regression, multiple discriminant and logit methods. The estimated models are then tested against the IPO data in the subsequent period between 1997-2000. The overall predictive ability of the forecasting models can be described as mediocre. In terms of actual abnormal returns obtained from investment strategies based on model predictions, only the logit models beat the outcome of naive strategies, albeit only marginally.