應用存活模型對於預測製造業購併事件之研究

The Application of Survival Model for Predicting Manufacturing Industry Merger and Acquisition

呂建霖(Chien Lin, Lu)

指導教授 ： 鍾麗英

國立臺北大學/商學院/統計學系/碩士(2008年)

摘要

近年來，全球各國公司之間的購併事件已非常普遍，而在實證研究的結果也發現到，購併公司往往在被購併時會有超額利潤的產生，因此如何準確的預測出這些將被購併的公司成為了一個熱門的研究議題。在本篇論文中，探討北美上市的製造業公司之購併事件，延續先前學者Palepu (1986)、Dietrich and Sorensen (1984)、Powell (1999)與Powell (2001)所提及的六大假說與選取變數對預測購併公司的研究，且利用於醫學統計中存活分析的離散時間危險模型與Cox比率危險模型，建構出一個新的預測購併公司方法，且做模型之間預測結果的比較。
由於存活模型用於財務領域上大多使用於破產的預測，很少用於購併公司的預測，所以本研究使用存活模型將是一大貢獻。而研究結果中發現到透過公司規模做分層所得到的Cox比率危險模型的預測能力優於離散時間危險模型與Cox比率危險模型，由於此模型考慮到時間相依的概念且公司規模大小的影響，使得預測正確的能力加以提升，希望此模型的使用與分析的結果能夠給予後進相關的研究一些參考。

關鍵字

購併 ； Cox比率危險模型 ； 離散時間危險模型

並列摘要

In the recent years, it is very common that M&A occurred among global companies. In the past empirical studies, we can find the excess return that appeared when a company was merged. Thus how to predict accurately these target firms has become a hot research issue. In this research, we discuss about the listed manufacturing companies in the North America, to extend the previous research of Palepu (1986), Dietrich and Sorensen (1984), Powell (1999) and Powell (2001), which discussed the six hypotheses and chose variables for predicting target firms.
Survival model is often applied in financial issues such as bankruptcy prediction, and rarely used in M&A prediction. The contribution of this study is to apply survival model in the M&A prediction research. In this study results, we can find that the forecasting accuracy of the stratified Cox proportional hazard model outperforms the discrete time hazard model and the Cox proportional hazard model. This model considers the time dependence influence and the firm size effect thus it enhances the forecasting accuracy. This study can be the reference material for the future research of predicting M&A issues.

並列關鍵字

M&A ； discrete time hazard model ； Cox proportional hazard model

參考文獻

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