dc.contributor.advisor | 馬秀如 | zh_TW |
dc.contributor.author (Authors) | 楊謹瑜 | zh_TW |
dc.creator (作者) | 楊謹瑜 | zh_TW |
dc.date (日期) | 2007 | en_US |
dc.date.accessioned | 2009-09-18 | - |
dc.date.available | 2009-09-18 | - |
dc.date.issued (上傳時間) | 2009-09-18 | - |
dc.identifier (Other Identifiers) | G0090353008 | en_US |
dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/34184 | - |
dc.description (描述) | 碩士 | zh_TW |
dc.description (描述) | 國立政治大學 | zh_TW |
dc.description (描述) | 會計研究所 | zh_TW |
dc.description (描述) | 90353008 | zh_TW |
dc.description (描述) | 96 | zh_TW |
dc.description.abstract (摘要) | 由於財務報表資訊易遭管理當局操縱,因此財務預警模型若僅考慮財務比率變數,即有其限制。本研究因此結合財務比率變數與公司治理變數,以期建構更良好的財務預警模型。此外,本研究使用倒傳遞網路為工具,以避免前述限制,並預期結果顯示綜合採用財務比率及公司治理二類變數,在預測期間短時,所建立的財務預警模型,其錯誤率的確較低。本研究同時發現,樣本公司中的危機公司大多屬於「急速失敗公司」。 | zh_TW |
dc.description.abstract (摘要) | Early warning models used to predict financial distresses of corporations confront with limitation, when the model specification consider only financial ratios based on financial statements, because of the possibility of manipulated financial statements. This study intends to construct a early warning model with not only financial ratio variables, but also corporate governance variables. The corporate governance variables may affect the corporation with financial distresses dramatically. This study constructs a new early warning model, considering the two kinds of variables, both financial ratio and corporate governance, and improves the predictability of sample firms of the one-quarter period. The study shows that Back Propagation Neural Network model can learn from the data of failed corporations and a matched group of survivor firms and hence predict the financial distresses. The study also finds the sample failed corporations are more likely to be “acute failure” ones.Keyword: BPN, Corporate Governance, Financial Distresses. | en_US |
dc.description.tableofcontents | 目錄第一章 概論 1第一節 研究背景與動機 1第二節 研究問題 4第三節 理論架構 5第四節 研究架構 6第二章 文獻探討 7第一節 會計相關文獻 7第二節 類神經網路相關文獻 16第三節 對本研究之啟示 24第三章 研究設計及研究方法 25第一節 財務危機之定義 25第二節 研究對象及期間 27第三節 變數定義 31第四節 BPN模型設計 36第五節 研究步驟 37第四章 實證分析及結果 38第一節 研究問題一 38第二節 研究問題二 40第三節 研究問題三 45第五章 結論與建議 48第一節 結論 48第二節 建議 50第三節 研究限制 51第四節 對後續研究之建議 52參考文獻 53 | zh_TW |
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dc.language.iso | en_US | - |
dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0090353008 | en_US |
dc.subject (關鍵詞) | 倒傳遞網路 | zh_TW |
dc.subject (關鍵詞) | 財務危機 | zh_TW |
dc.subject (關鍵詞) | 公司治理 | zh_TW |
dc.title (題名) | 企業財務危機預警模型之建構-以類神經網路為工具 | zh_TW |
dc.type (資料類型) | thesis | en |
dc.relation.reference (參考文獻) | 參考文獻 | zh_TW |
dc.relation.reference (參考文獻) | 一、 中文部分 | zh_TW |
dc.relation.reference (參考文獻) | 1. 呂紹強, 2000,企業財務危機預警模型之研究-以財務及非財務因素建構,當代會計,第一卷,第一期:p19-40 | zh_TW |
dc.relation.reference (參考文獻) | 2. 柯承恩,2000,我國公司監理體系之問題與改進建議(上) (下),會計研究月刊,173期:p74-81;174期:p79-83 | zh_TW |
dc.relation.reference (參考文獻) | 3. 郭瓊宜,1994,類神經網路在財務危機預警模式之應用,私立淡江大學管理科學研究所未出版碩士論文。 | zh_TW |
dc.relation.reference (參考文獻) | 4. 蔡秋田,1995,運用類神經網路預測上市營運困難之研究,國立成功大學會計研究所未出版碩士論文。 | zh_TW |
dc.relation.reference (參考文獻) | 5. 葉怡成,1999,應用類神經網路,台北;儒林圖書有限公司。 | zh_TW |
dc.relation.reference (參考文獻) | 6. 葉銀華、李存修與柯承恩,2002,公司治理與評等系統,台北:商智文化。 | zh_TW |
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dc.relation.reference (參考文獻) | 二、 英文部分 | zh_TW |
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