Predicting Merger and Acquisition Targets：An Empirical Study of Electronic Industry in Taiwan

• Main Authors: Chih-Wei Wang, 王智威
• Other Authors: 邱顯比
• Format: Others
• Language: en_US
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/82453991080881132971

碩士 === 國立臺灣大學 === 財務金融學研究所 === 95 === Firms may be merged or acquired for various reasons, some of these reasons are hypothesized and quantified into accounting, financial, or market variables. In previous studies, these variables were used to develop a target prediction model for foreign firms. The same concept is applied in this study to the Taiwan electronic industry. A forward stepwise binary logit regression is used to construct the model. Three different types of cutoff are used to test the classifying and predictive accuracy for the estimation sample and the holdout sample respectively. A portfolio of predicted targets is constructed using a cost-minimizing cutoff to test the possibility of earning excess returns from the model. The empirical results show that among six variables which are hypothesized to be important factors in predicting M&A targets, only three of them: net sales, return on equity, and retention rate, are found to be significant. The overall classifying and predicting accuracies of the model perform significantly better than pure chance, regardless of which cutoff is used. However, the ability of identifying M&A targets is quiet poor, indicating that it is difficult to earn excess returns from the model predictions. This conclusion is consistent with previous studies.