Improving Pricing Accuracy of the Abnormal Earnings Growth Model - Does a Fade-Away Factor Do the Trick?

Abstract: In this thesis, we examine whether the pricing accuracy of the parsimonious AEG model can be improved when industry-specific fade-away factors of AEG are acknowledged in the model. In order to answer this question, the study uses three different methods, namely a simple linear regression, a graph analysis, and a calculation of implied fade-away factors, to derive industry-specific patterns. Then, in a second step, these results are used to assess the AEG model's pricing accuracy with and with-out the acknowledgement of these industry-specific factors. It was found that industry-specific factors enhance the pricing accuracy of the AEG model. Especially the fade-away factors estimated with the linear regression proved to be superior. These findings contribute to previous studies which investigate the validity of the AEG model, and which hypothesize how it could be improved without adding unnecessary complexity. The fact that industry-specific fade-away factors have a significant impact on the AEG model's pricing accuracy highlights that both academic researchers and practitioners who engage with the AEG model should account for the industry-specific factors de-rived in this study.