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  1. NTU Theses and Dissertations Repository
  2. 管理學院
  3. 財務金融學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/38855
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor廖咸興
dc.contributor.authorTong-Li Chouen
dc.contributor.author周東立zh_TW
dc.date.accessioned2021-06-13T16:49:20Z-
dc.date.available2005-07-04
dc.date.copyright2005-07-04
dc.date.issued2005
dc.date.submitted2005-06-24
dc.identifier.citationAltman, E. I., 1968, “Financial Ratios, Discriminant Analysis, and the Prediction of Corporate Bankruptcy”, Journal of Finance 23, 589–609.
Altman, E. I., Anthony Saunders, 1998, “Credit Risk Measurement: Development over the Last 20 Years”, Journal of Banking and Finance, 21, 1721-1742.
Beaver, B., 1966, “Financial Ratios as Predictors of Failure”, Empirical Research in Accounting: Selected Studies, Supplment to Journal of Accounting Research Autumn, 91–101.
Black, Fischer and John C. Cox, 1976, “Valuing Corporate Securities: Some Effects of Bond Indenture Provisions”, Journal of Finance, 31, 351-367.
Caouette, John B., Edward I. Altman, and Paul Narayanan, 1998, Managing Credit Risk, John Wiley & Sons, Inc.
Chen, Ren-raw, 1996, Understanding and Managing Interest Rate Risks, World Scientific, chapter 5.
Chen, Tsung-Kang and Hsien-Hsing Liao, 2004, “A Cash Flow Based Multi-period Credit Risk Model”, Conference paper, A Paper Presented to the 12th Conference on the Theories and Practices of Securities and Financial Markets.
Coates, P. and L. Fant, 1991-2, “A Neural Network Approach to Forecasting Financial Distress”, The Journal of Business Forecasting, Winter, 9-12.
Dambolena, Ismael G., and Joel M. Shulman, 1988, “A Primary Rule For Detecting Bankruptcy: Watch The Cash”, Financial Analysts Journal, Sep/Oct, 74-78.
Duffie, Darrell, 1998, “Defaultable Term Structure Models with Fractional Recovery of Par”, Graduate School of Business, Stanford University.
Emery, Gary W., 1984, “Measuring Short-term Liquidity”, Journal of Cash Management, July/August.
Emery, Gary W. and Kenneth O. Cogger, 1982, “The Measurement of Liquidity”, Journal of Accounting Research, 20 (2), 290-303.
Emery, Gary W. and R. Lyons, 1991, “The Lambda Index: Beyond the Current Ratio”, Business Credit, Nov/Dec, 22-23.
Gallinger, George W. and P. Basil Healey, 1992, Liquidity Analysis and Management, Addison-Wesley Publishing Company.
Gombola, Michael J., Haskins, Mark E., Ketz, J. Edward, Williams, David D., 1987, “Cash Flow in Bankruptcy Prediction”, Financial Management, Winter, 55-65.
Hull, J. and A. White, 1995, “The Impact of Default Risk on the Prices of Options and Other Derivative Securities”, Journal of Banking and Finance, 19, 299-322.
Jarrow, Robert A., David Lando and Stuart M. Turnbull, 1997, 'A Markov Model for the Term Structure of Credit Risk Spreads', The Review of Financial Studies, 10 (1), 481-523.
Jarrow, Robert A. and Stuart M. Turnbull, 1995, “Pricing Derivatives on Financial Securities Subject to Credit Risk”, Journal of Finance, 50, 53-86.
Kallberg, Jarl G. and Kenneth L. Parkinson, 1993, Corporate Liquidity: Management and
Measurement, Richard D. Irwin.
Lando, David, 2004, Credit Risk Modeling, Princeton University Press.
Liao, Hsien-Hsing and Tsung-Kang Chen, 2005, “A Multi-period Corporate Short-term Credit Risk Model”, Review of Financial Risk Management, 1 (1), 61-86.
Litterman, Robert and T. Iben, 1991, “Corporate Bond Valuation and the Term Structure of Credit Spreads”, Financial Analysts Journal, Spring, 52-64.
Merton, Robert C., 1974, “On the Pricing of Corporate Debt: The Risk Structure of Interest Rates”, Journal of Finance, 2, 449-471.
Mossman, Charles E., Geoffery G Bell, L Mick Swartz, and Harry Turtle, 1998, “An empirical comparison of bankruptcy models”, The Financial Review, 33, 35-54.
McQuown J.A., 1997, “Market versus Accounting-Based Measures of Default Risk”, in I. Nelken, edited by, Option Embedded Bonds, Irwin Professional Publishing, Chicago.
Ohlson, J., 1980, “Financial Ratios and the Probabilistic Prediction of Bankruptcy”, Journal of Accounting Research, 19, 109–131.
Ralph B. D’Agostino and Michael A. Stephens, 1986, “Goodness-of-fit techniques”.
Shumway, T., 2001, “Forecasting Bankruptcy More Accurately: A Simple Hazard Model”, Journal of Business, 74, 101–124.
Wilson, T., 1997a, Portfolio Credit Risk, I. RISK 10, September, 111–117.
Wilson, T.,1997b, Portfolio Credit Risk, I. RISK 10, October, 56–61.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/38855-
dc.description.abstract近幾十年來,評估信用風險的文獻發展非常迅速。以模型的方法來說,可以粗分為兩大領域:會計基礎模型與市場基礎模型。然而在上述模型之中,很少能夠從公司財務資訊發展出有代表性的流動性指標來評估短期信用風險,更沒有進一步地以流動性指標為基礎建立隨機模型。除此之外,我們也很難找到模型可以同時內生產生流動性危機率 (probability of insolvency) 與預期流動性不足 (expected liquidity deficiency)。根據每單位資產流動性餘額 (以下簡稱LB/A) 的兩大特性—平均反轉以及可正可負,還有變化係數 (varying coefficient) 模型的概念,本研究建構出「狀態相依隨機流動性餘額模型」 (state-dependent stochastic liquidity balance model),以評估多期公司短期信用風險。本模型透過隨機產業經濟狀態模型產生的資訊,考慮了產業經濟狀態對一家公司LB/A結構的衝擊 (例如:流動性餘額模型的參數)。此流動性餘額模型可以模擬許多條LB/A路徑,並得出未來各期LB/A的分配。有了LB/A的分配與流動性危機的定義準則 (當LB/A小於零),我們可以推估出未來各期流動性危機率以及預期流動性不足。而對於外部投資者與債權人來說,本模型只需使用公開的公司財務資訊與產業經濟狀態資訊即可容易操作。最後,本研究的實證結果初步驗證了本模型的有效性。zh_TW
dc.description.abstractIn recent decades, literatures on credit risk measurement evolved dramatically. According to modeling techniques, they can be roughly grouped into two major categories, “accounting-based models” and “market-based models”. However, among the above models, few of them develop representative liquidity measure from corporate financial data to evaluate short-term credit risk and further build up a stochastic model based on the liquidity measure. In addition, we can hardly find a model that can generate probability of insolvency and expected liquidity deficiency endogenously and concurrently. Basing upon two significant characteristics of liquidity balance per unit asset (later denoted as LB/A) --“mean-reversion” and “allowing positive and negative values”, and the concept of varying coefficient model, the study constructs a “state-dependent stochastic liquidity balance model” to assess multi-period corporate short-term credit risk. It considers the impacts of industrial economic state changes on the structure of a firm’s LB/A process (i.e. the parameters of the liquidity balance model) through incorporating information generated from a stochastic industrial economic state model. The liquidity balance model can simulate many LB/A paths and then the LB/A distributions of each future period. With LB/A distribution and the criteria of insolvency (when LB/A is less than zero), we can obtain both the probability of a company’s liquidity crisis and the expected liquidity deficiency in future periods. In addition, for outside investors or creditors, this liquidity balance model is readily for them to perform a firm’s multi-period short-term credit risk analysis by using only publicly available information of corporate finance and the industrial economic state (i.e. the industrial cyclicality information). The empirical results of this study show preliminarily supports for the effectiveness of the model.en
dc.description.provenanceMade available in DSpace on 2021-06-13T16:49:20Z (GMT). No. of bitstreams: 1
ntu-94-R92723042-1.pdf: 451173 bytes, checksum: 3eef61487020903c4e8bf45e45c07664 (MD5)
Previous issue date: 2005
en
dc.description.tableofcontentsI. Introduction 1
II. State-dependent Stochastic Liquidity Balance Model 4
1. Liquidity Balance (LB) and liquidity balance per unit asset (LB/A) 5
2. Characteristics of liquidity balance per unit asset—normality and mean-reverting 7
3. Setting of state-dependent stochastic liquidity balance model 8
4. Parameters estimation 12
III. Multi-period Corporate Short-term Credit Risk Assessment 13
IV. Empirical Analysis 15
1. Data 15
2. Parameters estimation of the stochastic models of liquidity balance and industrial economic state 17
3. Empirical results of firm’s credit rating 17
V. Model’s Application in Pricing ABCP 21
VI. Summary and Conclusion 26
Reference…………………………………………………27
Appendix……………………………………………………29
dc.language.isoen
dc.subject流動性餘額zh_TW
dc.subject多期zh_TW
dc.subject信用風險zh_TW
dc.subject狀態相依zh_TW
dc.subjectstate-dependenten
dc.subjectliquidity balanceen
dc.subjectmulti-perioden
dc.subjectcredit risken
dc.title多期公司短期信用風險評估--狀態相依流動性餘額模型zh_TW
dc.titleMulti-period corporate short-term credit risk assessment--A state-dependent liquidity balance modelen
dc.typeThesis
dc.date.schoolyear93-2
dc.description.degree碩士
dc.contributor.oralexamcommittee李阿乙,林修葳,陳聖賢
dc.subject.keyword多期,信用風險,狀態相依,流動性餘額,zh_TW
dc.subject.keywordmulti-period,credit risk,state-dependent,liquidity balance,en
dc.relation.page43
dc.rights.note有償授權
dc.date.accepted2005-06-27
dc.contributor.author-college管理學院zh_TW
dc.contributor.author-dept財務金融學研究所zh_TW
顯示於系所單位:財務金融學系

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