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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 曾惠斌(Hui-Ping Tserng) | |
dc.contributor.author | Man-Cheng Lei | en |
dc.contributor.author | 李敏晶 | zh_TW |
dc.date.accessioned | 2021-06-13T17:29:58Z | - |
dc.date.available | 2016-08-09 | |
dc.date.copyright | 2011-08-09 | |
dc.date.issued | 2011 | |
dc.date.submitted | 2011-07-12 | |
dc.identifier.citation | Abidali, A. F. and Harris, F. (1995). 'A methodology for predicting company failure in the construction industry.' Construction Management and Economics, 13(3), 189 - 196.
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/39495 | - |
dc.description.abstract | 評估營建公司之信用風險在營建業之風險管理上是一個重要的議題,然而過去很少研究著重於評估營建公司之信用風險程度。由於現有的結構型信用風險模型與縮減型信用風險模型在應用上存在一些限制,並不能完全滿足營建業之信用風險評估之實務應用。對營建業而言,現金流量狀況能相當程度反應營建公司之償債能力。因此,本研究引用Liao & Chen (2006) 所發展出來的現金流量信用風險模型進行營建業之信用風險評量。本研究透過現金流量信用風險模型求出營建公司未來三年之信用風險分數後,與標準普爾(Standard and Poor)對各營建公司發出之信用評等作比較,衡量現金流量信用風險模型於各年判別信用風險高低之排序能力,以評斷使用此現金流量信用風險模型於營建業信用風險之適用性。
研究結果顯示,現金流量信用風險模型在未來一年之判別信用風險能力為優(AUC為0.8000),在未來二年、未來三年之判別信用風險能力在可接受之範圍內(AUC 分別為0.7765與 0.7647)。因此,現金流量信用風險模型適合運用於營建業之信用風險衡量上。另外,現金流量信用風險模型僅需要會計報表中的現金流資訊,適用於上市或非上市之營建公司,能更為廣泛地應用於營建業之信用風險評量上。由於現時信評機關只提供小部份營建公司之評等,現金流量信用風險模型能提供一快捷便利的方法供使用者對缺乏信用評等之營建公司作評量。 | zh_TW |
dc.description.abstract | Though assessing the credit risk of construction contractors is a crucial issue in construction risk management, few researches focus on credit risk assessment for construction industry. Due to some limitations in the existing credit risk models (the structure-form models and the reduced-form models), they do not fully satisfy the demands for the credit risk assessment of construction industry. Since cash flows to large extent reflect a contractor’s capacity to meet its financial obligations, this study employ a flow based credit model proposed by Liao and Chen (2006) to assess the credit qualities of construction contractors. This study employs the Area Under Curve (AUC) to evaluate the model’s discriminatory performances in ranking the credit qualities of construction contractors in three years using Standard and Poor’s issuer credit ratings as the benchmarks.
The empirical results show that the cash flow based credit model are with an excellent discriminatory performance in one year (AUC=0.8000) and with acceptable performances in 2 year (AUC: 0.7765) and 3 year (AUC: 0.7647). These indicate the cash flow based credit risk model is useful in assessing the credit quality of construction contractors. In addition, the cash flow based credit risk model is applicable in both listed and private construction contractors as it only requires information of accounting statements. Since only a small portion of construction contractors are rated by rating agency, the cash flow based credit model is especially useful in credit risk assessment of unrated construction contractors. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T17:29:58Z (GMT). No. of bitstreams: 1 ntu-100-R98521707-1.pdf: 1112232 bytes, checksum: f751a7ac64007aadf43ff476801d2298 (MD5) Previous issue date: 2011 | en |
dc.description.tableofcontents | ACKNOWLEDGEMENTS I
ABSTRACT IN CHINESE II ABSTRACT IN ENGLISH III TABLE OF CONTENTS IV LIST OF FIGUERS VII LIST OF TABLES VIII Chapter 1. Introduction 1 1.1 Background 1 1.2 Motivations and Problem Statements 3 1.2.1 Credit Risk Assessment for Construction Industry 3 1.2.2 The Unique Cash Flow Risk in Construction Industry 6 1.3 Purposes and Contributions 9 1.4 Procedure of the Research 10 1.5 Framework of the Thesis 10 Chapter 2. Literature Review 11 2.1 Credit Risk Models 11 2.2 Financial Ratio-Based Models 13 2.3 Free Cash Flow to Firm 20 2.4 Cash Flow Based Credit Model 23 2.5 Summary 25 Chapter 3. Methodology 26 3.1 Framework of Research Methodology 26 3.2 The Cash Flow Based Credit Model 29 3.2.1 A Firm’s State-Dependent Cash Flow Credit Model 29 3.2.2 Estimation of a Firm’s Weighted Average Cost of Capital 31 3.3 Model Evaluation Approach (ROC curve) 32 3.4 Summary 33 Chapter 4. Data Collection and Empirical Application 34 4.1 Data and Sample Selection 34 4.2 Free Cash flow Proxy and Data Summary 38 4.3 Factor Analysis and Parameter Estimations of the State Model 39 4.4 Parameters Estimations of the Present Value Model 41 4.4.1 Estimation of a Firm’s Weighted Average Cost of Capital 41 4.4.2 Estimation of Constant Growth Rate of a Firm 43 4.4.3 Estimation of the Shift Term to a Firm’s Cash Flow Paths 43 4.5 The Setting of Default Thresholds 45 4.6 Credit Quality Score and Model Discriminatory Power 46 4.7 Summary 50 Chapter 5. Conclusions 51 References 54 Appendixes 60 Appendix I US Business Cycle Expansions and Contractions (NBER) 60 Appendix II The Description of Standard & Poor's Issuer Credit Ratings Categories (Compustat Database) 61 Appendix III The Time Series of Free Cash Flow Pattern of Construction Firms 63 Appendix IV Factor Analysis of Firm’s Free Cash Flows 66 Appendix V Maximum Likelihood Algorithm for Factor Generating Formula 70 Appendix VI Cash Flow Shift Term Estimates 72 | |
dc.language.iso | en | |
dc.title | 運用現金流量信用風險模型評估營建公司之信用風險-以美國營建公司為例 | zh_TW |
dc.title | Assessing the Credit Risk of Construction Contractors Using Cash Flow Based Credit Model | en |
dc.type | Thesis | |
dc.date.schoolyear | 99-2 | |
dc.description.degree | 碩士 | |
dc.contributor.coadvisor | 廖咸興(Hsien-Hsing Liao) | |
dc.contributor.oralexamcommittee | 晁立中(Li-Chung Chao),陳維東(Wei-Tong Chen) | |
dc.subject.keyword | 營建業,信用風險,現金流模型,ROC 曲線, | zh_TW |
dc.subject.keyword | construction industry,credit risk,cash flow based credit model,ROC curve, | en |
dc.relation.page | 73 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2011-07-12 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 土木工程學研究所 | zh_TW |
顯示於系所單位: | 土木工程學系 |
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