Testing cumulative prediction errors in event study methodology

This paper reconsiders event study methodology, a very popular technique in the applied finance literature, within the context of testing cumulative prediction errors. It extends the conventional test statistics in two directions. First, it accounts fully for the increased variance of prediction errors outside of the estimation period and for the cumulation of these errors across different event windows. Second, it also takes account of the fact that market model residuals are typically serially correlated, heteroscedastic and non-normal. The statistics are compared with the conventional approach by reassessing a previous application of the methodology to the impact of management buyouts.