台灣新上市櫃公司存活之預警模式研究

An Exploration of Prediction Model on Initial Public Offerings Survival in Taiwan

陳建勝(Jai-Shen Chen) ； 陳美菁(Mei-Ching Chen) ； 劉家宏(Chia-Hong Liu)

《智慧科技與應用統計學報》 8卷1期 (2010/06) Pp. 27-40

https://doi.org/10.29807/JTITAS.201006.0003

摘要

以往在IPO的研究多在探討其超額報酬，但IPO市場存在著嚴重資訊不對稱的問題，其風險面更顯得重要，故本研究以市場資訊、股權結構及財務績效探討影響台灣新上市櫃公司夫敗之因素，並以邏輯特迴歸和Bortiz and Kenndy (1995)的誤判成本來判別不同臨界值下各模型之優劣。研究結果發現，以0.15作為模型之臨界值可得到相對最小之誤判成本，最後實證結果發現新上市櫃公司的簽證會計師事務所、財務槓稈、每股盈餘和交易市場類別與台灣新上市櫃失敗有顯著關係，此預警模型之正確區別能力達81.5%。

關鍵字

存活 ； 邏輯特迴歸 ； 誤判成本

並列摘要

The previous studies mostly explore the excess return on IPO. However, the risk is more important in IPO market since information asymmetry is more serious. Therefore, this study adopts market information, ownership structure and financial performance to explore the factors of failure in IPOs in Taiwan. Logic regression model and misclassification cost of Bortiz and Kennedy (1995) are used to compare the performances among models with different cut-off values. The results reveal that model with 0.15 cut-off value obtain relatively minimum misclassification cost. Finally, the significant variables that would affect the IPOs are CPA firms, financial leverage, EPS and market listing of categories. The accurate rate of classification in this prediction model is 82.9%.

並列關鍵字

survival ； logic regression model ； misclassification cost