請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/92701完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 王泰昌 | zh_TW |
| dc.contributor.advisor | Tay-Chang Wang | en |
| dc.contributor.author | 高嘉鴻 | zh_TW |
| dc.contributor.author | Jia-Hong Gao | en |
| dc.date.accessioned | 2024-06-13T16:06:10Z | - |
| dc.date.available | 2024-06-14 | - |
| dc.date.copyright | 2024-06-13 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-06-11 | - |
| dc.identifier.citation | 張紹勳. (2018). 邏輯斯迴歸及離散選擇模型：應用STaTa統計. 五南圖書出版股份有限公司.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/92701 | - |
| dc.description.abstract | 本研究旨在比較扣除所得稅、利息、折舊及攤銷前利潤率（EBITDA利潤率）及營業利益率於預測危機企業之表現並判斷EBITDA利潤率是否為較佳之財務危機預測因子。研究樣本取自台灣經濟新報(TEJ)資料庫，並以2008年至2022年間之上市櫃企業作為研究對象，使用Logit迴歸分析及Probit迴歸分析來檢測EBITDA利潤率及營業利益率於財務危機發生前三年間之反應能力。研究結果指出，EBITDA利潤率及營業利益率於兩種統計方法下之預測能力並無顯著差異，雖然EBITDA利潤率最終模型及營業利益率最終模型於危機前三年內之整體預測準確率均達90%以上之水準，型一誤差(%)卻表明預測危機企業之能力仍不理想，顯示EBITDA利潤率無法作為危機判別之重要預測指標。另外，相關實證結果亦表明Logit迴歸分析於危機前二年內之預測表現略優於Probit迴歸分析，而隨著預測時點之接近，二最終模型之預測錯誤成本均呈現逐漸上升之跡象，顯示模型早期之預警效果較佳。 | zh_TW |
| dc.description.abstract | This study aims to compare the effectiveness of the EBITDA margin and the operating profit margin in predicting financially distressed companies and to determine if the EBITDA margin is a better predictor of financial crises. The research sample is taken from the Taiwan Economic Journal (TEJ) database and focuses on listed companies from 2008 to 2022. Logistic regression analysis and Probit regression analysis are used to examine the responsiveness of the EBITDA margin and the operating profit margin during the three years preceding a financial crisis. The results indicate that there is no significant difference in predictive ability between the EBITDA margin and the operating profit margin under both statistical methods. Although both the final EBITDA margin model and the final operating profit margin model achieved an overall prediction accuracy of over 90% within the three years preceding the crisis, Type I error (%) suggests that the ability to predict distressed companies is still not ideal. This implies that the EBITDA margin cannot be considered an important predictive indicator of crises. Additionally, empirical results show that Logistic regression analysis performs slightly better than Probit regression analysis in the two years before the crisis. As the prediction point approaches, the prediction error costs of both final models tend to increase, indicating that the early warning effect of the models is better. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-06-13T16:06:10Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-06-13T16:06:10Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 摘要 i
Abstract ii 目次 iii 圖次 v 表次 vi 第一章 緒論 1 第二章 文獻回顧 3 第一節 EBITDA介紹 3 第二節 企業財務危機定義 4 第三節 財務危機預警模型之相關文獻 6 一、 單變量分析（Univariate analysis） 7 二、 多變量區別分析（Multivariate discriminant analysis） 7 三、 Logit迴歸分析（Logistic regression analysis） 9 四、 Probit迴歸分析（Probit regression analysis） 10 五、 類神經網路（Artificial neural network） 11 六、 資料包絡分析（Data envelopment analysis） 12 七、 存活分析（Survival analysis） 12 八、 支持向量機（Support vector machine） 13 第三章 研究設計 17 第一節 資料來源及樣本選取 17 第二節 研究變數定義 22 一、 依變數（Dependent variable） 22 二、 自變數（Independent variable） 22 三、 控制變數（Control variable） 22 第三節 研究方法及模型建構 22 一、 Logit迴歸模型 22 二、 Probit迴歸模型 23 第四節 模型檢驗 24 一、 概似比檢定（Likelihood ratio test） 24 二、 偽R2（Pseudo R2） 24 三、 卡方檢定（Chi-squared test） 25 四、 赤池信息量準則（Akaike information criterion） 25 第五節 模型準確度檢測 25 一、 混淆矩陣（Confusion matrix） 25 二、 ROC曲線（Receiver operating characteristic curve） 26 第六節 預測錯誤成本 27 第四章 實證結果分析 28 第一節 敘述性統計 28 第二節 Logit迴歸模型 33 一、 Logit危機前一年 33 二、 Logit危機前二年 33 三、 Logit危機前三年 34 第三節 Probit迴歸模型 35 一、 Probit危機前一年 35 二、 Probit危機前二年 35 三、 Probit危機前三年 36 第四節 預測準確度之比較 49 一、 危機前一年 49 二、 危機前二年 50 三、 危機前三年 51 第五節 預測錯誤成本分析 64 第六節 預測有效性測試 65 一、 危機前一年 68 二、 危機前二年 69 三、 危機前三年 69 四、 預測錯誤成本 71 第五章 結論與建議 74 參考文獻 76 附錄一 ROC曲線 82 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | 財務危機預警模型 | zh_TW |
| dc.subject | 預測錯誤成本 | zh_TW |
| dc.subject | EBITDA利潤率 | zh_TW |
| dc.subject | 擬制性盈餘 | zh_TW |
| dc.subject | 混淆矩陣 | zh_TW |
| dc.subject | financial early warning models | en |
| dc.subject | confusion matrix | en |
| dc.subject | EBITDA margin | en |
| dc.subject | prediction error costs | en |
| dc.subject | pro-forma earnings | en |
| dc.title | 企業財務危機預警模型—EBITDA利潤率與營業利益率之分析 | zh_TW |
| dc.title | Financial Early Warning Model—Analysis of EBITDA Margin and Operating Margin | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.coadvisor | 劉嘉雯 | zh_TW |
| dc.contributor.coadvisor | Chia-Wen Liu | en |
| dc.contributor.oralexamcommittee | 曾怡潔;林瑞青 | zh_TW |
| dc.contributor.oralexamcommittee | Yi-Jie Tseng;Ruey-Ching Lin | en |
| dc.subject.keyword | 財務危機預警模型,擬制性盈餘,EBITDA利潤率,混淆矩陣,預測錯誤成本, | zh_TW |
| dc.subject.keyword | financial early warning models,pro-forma earnings,EBITDA margin,confusion matrix,prediction error costs, | en |
| dc.relation.page | 84 | - |
| dc.identifier.doi | 10.6342/NTU202401130 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2024-06-12 | - |
| dc.contributor.author-college | 管理學院 | - |
| dc.contributor.author-dept | 會計學系 | - |
| dc.date.embargo-lift | 2029-06-11 | - |
| 顯示於系所單位： | 會計學系 | |
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