| Summary: | 碩士 === 國立臺灣大學 === 財務金融學研究所 === 100 === Capital stock downsizing with cash refunding to shareholders seems to be effective in enhancing stockholder’s equity and reducing agency problems. The first case of this type occurs in 2002 and until 2009 there have been 47 cases. Literatures have so far focused on differences between three kinds of capital reductions and their announcement effect, abnormal return or post-downsizing performance of cash capital reduction. This research concentrates soly on cash capital reduction event, and builds two empirical models for paired samples and non-paired samples. Both empirical models found significantly different sample means in several financial variables. These variables are then applied to discriminant analysis and binary logistic regression to classify and predict cash capital reduction.
We find that paired samples are more suitable than non-paired samples for they are not affected by sample size and industry factors. When it comes to variable selection, stepwise method is good at in-sample classification while significant means method is useful in out-sample prediction. Debt ratio and price-to-book ratio are found to be the most significant variables in explaining downsizing decision. Besides, discriminant method has higher cash capital reduction accuracy whereas binary logistic method has higher non-cash capital reduction accuracy. No matter which multivariate method is used, the predict accuracy of cash capital reduction is above 80% which is higher than the predict accuracy of non-cash capital reduction of 40%. The overall accuracy ranges from 60% to 70% plus.
|
|---|
