| dc.contributor.advisor | 蔡政憲 | zh_TW |
| dc.contributor.author (Authors) | 尹立慶 | zh_TW |
| dc.creator (作者) | 尹立慶 | zh_TW |
| dc.date (日期) | 2005 | 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) | G0923580261 | en_US |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/34173 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 風險管理與保險研究所 | zh_TW |
| dc.description (描述) | 92358026 | zh_TW |
| dc.description (描述) | 94 | zh_TW |
| dc.description.abstract (摘要) | 信用風險長久以來是學術和實務研究的重要議題，而以往的研究常常著重在違約機率的計算與探討;而另一方面，在信評公司的系統性的評估下，信用評等的發佈適時地提供了提供了利害關係人另一種信用風險的客觀參考指標。本文採用Moodys所研發的PFM模型(Private Firm Model，針對未上市櫃公司的KMV模型)進行台灣金融產業中未上市櫃銀行的研究，計算各被研究公司的違約距離，再加以分組比較，計算出依此模型所求出之內部信用評等分級。由於信用評等公司所採用的評等方式多是利用已發生的財務資訊以資產品質、獲利能力、通路、風險管理能力和資本結構進行，以訪談的方式進行，其中人為主觀的成分往往無法客觀的屏除。然若可以採用股價所隱含的資訊進行分析，理論上應可以反應一家公司所有財務和非財務的資訊。本研究即試圖找出未上市櫃公司之應有股價，用以進行風險的分析研究，此即為PFM模型之精神。最後，在有效建立出台灣未上市櫃銀行之信用分佈後，本文進一部將模型所預測出的信用評等與中華信評之既有信評歷史交叉分析以檢視兩模型之關係，研究結果顯示，加入金控的銀行具有與信評較為一致的信用評等，未加入金控銀行之信用評等則俱較明顯的不同。 | zh_TW |
| dc.description.abstract (摘要) | Credit risk has been long interested by scholars and practitioners in ways of different measures, especially probability of default; on the other hand, credit rating agencies such as S&P, Moodys, and Fitch also provide rating reports in a timing manner for interested parties for diverse purposes. This paper adopted Moodys’ PFM (Private Firm Model, based on KMV model for listed corporation) for exploring Taiwan’s unlisted banks’ distance to default (DD) in a bid to create our internal rating model for each bank’s credit profile. Basically, rating agencies utilize historical financial and non-financial information in terms of asset quality, profitability, risk management, and capitalization as well by in-depth interviews to assess companies’ credit, however, exclusion of fully subjective appraisers’ opinions is questioned. In contrast, stock price should, theoretically, contain sophisticated information both financially and non-financially for credit research, which is the spirit of PFM’s credit assessment. In the final session, this paper will compare credit ratings generated from internal rating model with the ratings assigned by Taiwan Ratings’ to study the correlation between these two models. It concludes that FHC-based banks have similar credit ratings as Taiwan Ratings’ but not non-FHC-based ones. | en_US |
| dc.description.tableofcontents | 第一章 緒論 5第一節 前言 5第二節 研究流程 8第二章 研究方法 9第一節 KMV Credit Monitor Model 9第二節 Private Firm Model (PFM) 11第三節 違約距離與預期違約機率的估算： 13第三章 實証結果 14第一節 樣本選取 14第二節 上市公司之實證結果 17第三節 PFM實証結果 19第四節PFM模型以台灣銀行業為主之比較 25第四章 結論與建議 30 | 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/#G0923580261 | en_US |
| dc.subject (關鍵詞) | PFM | en_US |
| dc.title (題名) | 台灣未上市櫃銀行違約風險預測-以KMV公司之PFM模型為例 | zh_TW |
| dc.type (資料類型) | thesis | en |
| dc.relation.reference (參考文獻) | 中文 | zh_TW |
| dc.relation.reference (參考文獻) | 許士偉，利用PFM衡量我國未上市保險公司之違約風險，政治大學風險管理與保險研究所論文，民94年6月 | zh_TW |
| dc.relation.reference (參考文獻) | 黃仁德、陳淑郁，信用風險衡量，台灣金融財務季刊，第五輯，第三期，民93年9月，77-111。 | zh_TW |
| dc.relation.reference (參考文獻) | 陳侑宣，商業銀行如何使用信用風險值檢視授信政策，中央大學財務金融研究所碩士論文，民93年6月 | zh_TW |
| dc.relation.reference (參考文獻) | 周培如，銀行危機預警指標-KMV信用風險模型與財務指標之應用，政治大學經濟研究所碩士論文，民92年6月 | zh_TW |
| dc.relation.reference (參考文獻) | 王懷德，KMV模型於國內未上市、未上櫃之公開發行公司之研究，東吳大學會計研究所論文，民92年6月。 | zh_TW |
| dc.relation.reference (參考文獻) | 陳思翰，商業銀行如何利用Logit及KMV模型檢視授信政策，中央大學財務金融研究所碩士論文，民92年6月 | zh_TW |
| dc.relation.reference (參考文獻) | 林妙宜，公司信用風險之衡量，政治大學金融研究所碩士論文，民91年6月。 | zh_TW |
| dc.relation.reference (參考文獻) | 楊士昌，壽險業信用評等模式之研究-美國壽險公司之實證分析，政治大學風險管理與保險研究所論文，民91年6月 | zh_TW |
| dc.relation.reference (參考文獻) | 施佳華，產險業信用評等模式之研究－美國產險公司之實證分析，政治大學風險管理與保險研究所論文，民90年7月 | zh_TW |
| dc.relation.reference (參考文獻) | 英文 | zh_TW |
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| dc.relation.reference (參考文獻) | 2. Douglas W. Dwyer, 2005, “Examples of Overfitting Encountered When Building Private Firm Default Prediction Models”, MKMV White Paper. | zh_TW |
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