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  1. NTU Theses and Dissertations Repository
  2. 工學院
  3. 土木工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/17965
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor曾惠斌
dc.contributor.authorChing-Yuan Huangen
dc.contributor.author黃靖媛zh_TW
dc.date.accessioned2021-06-08T00:47:15Z-
dc.date.copyright2015-09-02
dc.date.issued2014
dc.date.submitted2015-07-26
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/17965-
dc.description.abstract信用風險管理是一個對業主及營建公司雙方都非常重要的事,信用危機的發生,往往對雙方造成龐大的損失。因此建立一套信用風險管理對雙方而言是個非常重要的課題,風險預審的目的是挑選出最適合的廠商或者業者,進而減少工程失敗的風險,審查標準包含了技術、管理能力、安全考量、環境及財務狀況,其中營建公司現金流量是一個最重要因素,現金流動不僅會使營建公司無法如期履行其債務,進而導致公司面臨週轉困難,甚至破產,這將使造成建設中工程延緩或者失敗。
今日業主廣泛使用會計信用評分法以及財務信用評分法來對營建公司進行財務風險的評估,但會計信用評分法所使用的財報內容容易被人為操控,而且有時間落差的現象。而財務信用評分法的主要基礎是以股票所反應出的公司價值為主,並且假設公司所有的價值是如實反應在股票市場上,但現實上股票時常未能正確反應出公司的價值。
本研究藉結構型現金流量基礎模型來對營建公司的財務風險進行分析,公司的財務風險與其是否有足夠現金來週轉其債務有高度關聯,本研究導入結構型現金流量基礎模型來模擬該公司的信用風險分數,業主可利用此分數來判別該建商是否符合財務資格,由於結構型現金流量基礎模型僅需要財報中的現金流量做為評計基礎,此模型適用於上市及非上市營建公司。
本研究模擬出營建公司未來三年的財務信用風險,然後將之與各公司標準普爾(Standard and poor)信用等級做比較,本研究同時借用接受者操作特性曲線(R.O.C.)來評估本模型的辨別能力,研究結果第一年AUC:0.8833,第二年AUC:0.85,及至第三年AUC:0.85,R.O.C.結果證實結構型現金流量基礎模型是適用於營建業的財務風險評估,本研究期望此模型能建立成一個適合於營造業的財務預警分析模型,業主能藉此模型更準確篩選出財務能力佳的營建公司。
zh_TW
dc.description.abstractEvaluating a company’s financial health has always been a difficult proposition for construction industry. Credit risk evaluation challenges investors, financial institutions and academics alike. The construction industry has come to rely on two distinguished credit risk evaluation methods: the accounting-based method depends on a corporate balance sheet as a guide, whereas the market-based model relies on market information to predict financial distress. However, present credit risk evaluation models have their limitations. A corporate balance sheet is easily manipulated by management, and the market information method is based on the presumption that stock price is a full reflection of market information, which is doubtful even among scholars.
This study evaluates a cash flow-based credit model proposed by Liao and Chen (2006). This model uses free cash flow to predict the credit qualities of construction contractors. In addition, this study uses the Area Under Curve (AUC) to determine the model’s discriminatory Performance. The Model’s performance will be benchmarked against Standard and Poor’s credit rating of the sample construction contractors.
The empirical results indicate that the cash flow-based model has an excellent discriminatory power: AUC = 0.8833 in the first year, AUC = 0.85 in the second year and AUC = 0.85 in the third year. This model proves to be a useful tool in assessing the credit risk of construction Contractors. It is both applicable in listed and private construction contractors since this model only needs the information from accounting statements.
en
dc.description.provenanceMade available in DSpace on 2021-06-08T00:47:15Z (GMT). No. of bitstreams: 1
ntu-103-P01521708-1.pdf: 1404952 bytes, checksum: 1fbc21c3e23c47a6ecc480f5d8376995 (MD5)
Previous issue date: 2014
en
dc.description.tableofcontents口試委員審定書………………………………………………………......... ……. ……..... i ACKNOWLEDGEMENTS ………………………………………………………...............ii
ABSTRACT IN CHINESE ……………………………………………………………...... iii
ABSTRACT IN ENGLISH ………………………………………………………………. iv
TABLE OF CONTENTS ……………………………………………………………....... v
LIST OF FIGURES …………………………………………………………………...… viii
LIST OF TABLES ……………………………………………………………………... ix
Chapter 1. Instruction …………………………………………………………………….... 1
1.1 Background ………………………………………………………………….... 1
1.2 Motivations and Problem Statements ……...……………………………...…...2
1.2.1 Credit Risk Assessment for the Construction Industry…….............. 3
1.2.2 The Unique Financial Risk in Construction Industry ……...……... .4
1.3 Purpose and Contributions …………………………………………………... ..7
1.4 Research Procedure ………………………………………………………..… ..8
1.5 Framework of the Thesis …………………………………………………..…...8
Chapter 2. Literature Review ……………………………………………………………. ..9
2.1 Structural-Model …………………………………………….………...……......9
2.2 Reduced-form Models ...…………………………………….………………... 10
2.3 Financial Ratio-Based Models …………………………….…………………. 10
2.4 Cash Flow Based Multi-Period Credit Model …………….……………..…… 14
2.5 Summary ………….………………………………………………………….. 17
Chapter 3. Methodology …………………………………………………………………. 18
3.1 Research Methodology ………………………………………………………. 18
3.2 The Characteristics of a Firm’s Free Cash Flow ……………………….......... 22
3.3 Cash Flow Based Multi-Period Credit Model ……………………………….. 24
3.3.1 Estimation of the State Factor Parameters ………………………….. 24
3.3.2 Estimation of a Firm’s Multi-Period Cash Flow ……………...…..... 25 3.3.3 Estimation of a Firm’s Weighted Average Cost of Capital …………. 26
3.3.4 Estimating a Firm’s Multi-Period Asset Distribution …………..…... 27
3.4 Default Threshold …………………………………………………………..… 27
3.5 Credit Quality Score ………………………………………………………….. 29
3.6 Model Evaluation (ROC curve) ……….……………………………...…….... 30
3.7 Summary ……………………………………………………………………... 31
Chapter 4. Empirical Application ……………………………………………………….. 33
4.1 Data and Collection ………………………………………………………….. 33
4.2 The Selection of Cash Flow Proxy …………………………………………... 36
4.3 Factor Analysis and Parameter Estimations of the State Factor ………..……. 37
4.4 Estimation of a Firm’s Weighted Average Cost of Capital …………….…….. 39
4.5 Estimation of Constant Growth Rate ……………………………………….... 41
4.6 Estimation of the Shift Term to a Firm’s Cash Flow Paths ………………….. 41
4.7 The Setting of Default Thresholds …………………………………………... 43
4.8 Credit Quality Score and Model Discriminatory Power …………………….. 44
4.9 Summary …………………………………………………………………….. 49
Chapter 5. Conclusions …………………………………………………………………... 51
References ………………………………………………………………………………... 54
Appendixes ……………………………………………………………………………….. 60
Appendix I The Description of Standard & Poor’s Issuer Credit Ratings Categories
(Source : Compustat Database) …………………………………………………... 60
Appendix II The Time Series of Free Cash Flow Pattern of Construction Firms ... 62
Appendix III Factor Analysis of Firm’s Free Cash Flows ……………………….. 66
Appendix IV Maximum Likelihood Algorithm for Factor Generating Formula ... 69
Appendix V Cash Flow Shift Term Estimates ……………..…………………….. 71








LIST OF FIGURES
Figure 1.1 Procedure of Research ……………………………………………………….. .8
Figure 3.1 Flowchart of Methodology …………………………………………………... 20
Figure 3.2 Flowchart of Cash Flow Based Multi-Period Credit Model …………………. 21
Figure 3.3 Free Cash to Firm per unit asset ……………………………………...……… 23
Figure 3.4 An example of a ROC curve …………………………………………………. 31
Figure 4.1 AUC Result of Cash Flow Based Multi-Period Credit Model in 1-Year ...…... 47
Figure 4.2 AUC Result of Cash Flow Based Multi-Period Credit Model in 2-Year …...... 47
Figure 4.3 AUC Result of Cash Flow Based Multi-Period Credit Model in 3-Year …….. 48







LIST OF TABLES
Table 4.1 List of Construction Firms …………………………………………...………. 35
Table 4.2 Parameters Estimations for State Factor Process ……………………..……... 38
Table 4.3 The Estimation Results of Each Firm’s WACC ……………………………… 40
Table 4.4 The Estimation Results of Each Contractor’s Implied Cash Flow Shift Term 42
Table 4.5 Calculation Result of Each Firm’s Default Boundary …………………………. 44
Table 4.6 Credit Quality Score ……………………………………………………….…... 45
Table 4.7 AUC of Cash Flow Based Multi-Period Credit Model ……………….……….. 46
Table III-1 Factor Extraction ………..……………………………...……………….……. 66
Table III-2 Factor Loading .………………………….………………………….…….... 67
Table III-3 State Factor Values ….………………….…………………………………….. 68
dc.language.isoen
dc.title運用現金流量模式篩選財務健全公司zh_TW
dc.titlePrequalifying Financial Competent Company
by Cash Flow Credit Model
en
dc.typeThesis
dc.date.schoolyear103-2
dc.description.degree碩士
dc.contributor.oralexamcommittee周瑞生,林祐正,黃文顥
dc.subject.keyword營建公司,信用風險,現金流量基礎模型,zh_TW
dc.subject.keywordconstruction industry,credit risk evaluation,cash flow-based structure model,en
dc.relation.page78
dc.rights.note未授權
dc.date.accepted2015-07-27
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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