:::

詳目顯示

回上一頁
題名:住宅抵押貸款逾期率之廣義線性模型研究
作者:陳宗豪 引用關係
作者(外文):Tsung-Hao Chen
校院名稱:國立高雄第一科技大學
系所名稱:管理研究所
指導教授:林左裕
楊顯爵
學位類別:博士
出版日期:2007
主題關鍵詞:住宅抵押貸款逾期放款敏感度指定度機率界限接受者作業特徵曲線residential mortgage loansnon-performancesensitivityspecificitycutoff pointreceiver operating characteristic curve
原始連結:連回原系統網址new window
相關次數:
  • 被引用次數被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:0
  • 共同引用共同引用:0
  • 點閱點閱:26
本研究旨在應用廣義線性模型中之羅吉斯廻歸模型,以改善國內不動產抵押債權逾期模型,其中包括考慮總體經濟因素及尋找較佳之機率界限(cutoff point)以增加逾期預測準確率。資料來源採用國內某大型行庫之住宅貸款資料,觀察期間為1985年元月至2006年12月。應用羅吉斯廻歸模型時,採用總體經濟因素(包含經濟成長率、失業率及利率);這三個變數中,經濟成長率及失業率分別採取依行政院主計處資料提供,以逾期或期滿結案時的經濟成長率(失業率)減撥貸時經濟成長率(失業率)之差額列入計算。經由多元共線性(multicollinearity)及特異値(outliers)與特殊影響之觀察值(influential observations)診斷後,並採用敏感度(sensitivity)與指定度(specificity)交叉點預測方法,找出最適的機率界限,以穩定逾期預測準確率及正常預測準確率之預測程度;並輔以接受者作業特徵曲線(ROC curve)方法分析預測能力。
實證結果顯示,當模型僅含貸款者特質及借款契約條件時,加入總體經濟因素可以提高對住宅抵押貸款逾期之預測能力,在模型適合度及模型預測能力,皆相對改善僅含「貸款者特質及借款契約條件」,故亦佐證外商銀行房屋貸款授信參酌總體經濟因素指標有其合理性與實用性。
This dissertation aims to enhance the predictability of a logistic model, which is frequently fitted for residential mortgage loans. The improvements include incorporating three indexes–interest rate, economic growth rate and unemployment rate–and comparing the cutoff points of the probabilities for classifying a loan as default versus non-default. For economic growth rate and unemployment rate, we use the spread (instead of original rates) between the rate when a loan is granted and the one when it matures or defaults. The data set contains 2658 loans which were observed between Jan. 1985 and Dec. 2006 in a large commercial bank in Taiwan.
In fitting the model, multicollinearity is diagnosed, and outliers and influential observations are screened. Specificity and sensitivity are analyzed for comparing the cutoff point probabilities of predicting a default loan. These comparisons are also analyzed with receiver operating characteristic curve (ROC curve).
Our results show that, with the borrower’s characteristics and lending contract conditions in the model, the indexes such as interest rate, economic growth rate and unemployment rate can enhance the accuracy for predicting a default loan. This finding is consistent with the practice of some foreign banks in Taiwan, in which case they ceased the mortgage business in the mid- 1990s while the economy was expected to decline in Taiwan.
1. 王濟川、郭志剛 (2004)。Logistic廻歸模型-方法及應用。台北:五南圖書。
2. 李桐豪、呂美慧 (2000)。金融機構房貸客戶授信評量模式分析 – Logistic廻歸之應用。台灣金融財務季刊,1(1),1-20。new window
3. 林左裕 (2004)。台灣住宅抵押貸款終止行為之研究。農業經濟半年刊,76,169-195。
4. 林左裕、劉長寬 (2003)。應用Logit模型於銀行授信違約行為之研究。2003年中華民國住宅學會學術論文研討會,台北大學,台北。
5. 林左裕、賴郁媛 (2005)。我國銀行業逾放比與總體經濟因素間關係之研究。商管科技季刊, 6(1),165-179。new window
6. 林師模、陳苑欽 (2004)。多變量分析-管理上的應用。台北:雙葉書廊。new window
7. 馬君梅 (2003)。財報分析應用於信用風險的發展趨勢。會計研究月刊,214,84-94。
8. 陳建仁 (2000)。流行病學:原理與方法。臺北:聯經出版事業公司。
9. 曾銘宗 (2000)。逾期放款比率與經濟成長率及失業率間關係之研究。存款保險資訊季刊, 14(1),140-149。new window
10. 黃仁德、陳淑郁 (2005)。信用風險衡量理論與實務 。台北:財團法人中華民國證券暨期貨市場發展基金會。new window
11. 劉代洋、李馨蘋 (1994)。購屋貸款與家戶社經特色之實證研究-以台中都會區為例。管理科學學報, 11(1),109-127。
12. 盧秋玲、郭姿伶 (2000)。住宅貸款之提前清償與逾期還款。中國財務學會2000年研討會,台灣大學,台北。
13. Agresti, A. (1996). An introduction to categorical data analysis. New York: John Wiley.
14. Agresti, A. (2002). Categorical data analysis (2nd ed.). New York: John Wiley.
15. Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle. In B. N. Petrov & F. Csaki (Eds.), Second International Symposium on Information Theory: (pp. 267-282). Budapest, Hungary: Akademiai Kiado.
16. Albert, J. H., & Chib, S. (1993a). Bayesian analysis of binary and polychotomous response data. JASA, 88(422), 669-679.
17. Albert, J. H., & Chib, S. (1993b). Bayes inference via Gibbs sampling of autoregressive time series subject to Markov mean and variance shifts. Journal of Business and Economics Statistics, 11(1), 1–15.
18. Allison, P. D. (1999). Logistic regression using the SAS system: Theory and application. Cary, NC: SAS Institute.
19. Berry, W. D., & Feldman, S. (1985). Multiple regressions in practice. Newbury Park, CA: Sage Publications.
20. Canner G. B., Gabriel, S. A., & Woolley, J.M. (1991). Race, default risk and mortgage lending: A study of the FHA and conventional loan markets. Southern Economic Journal, 58(1), 249-262.
21. Claureite, T. M. (1990). A note on mortgage risk: Default vs. loss rate. AREUEA Journal, 18(2), 202-206.
22. Collect, D. (2003). Modeling binary data (2nd ed.). London: Chapman & Hall.
23. Deng, Y. H., Quigley, J. M., & Van Order, R. (1996). Mortgage default and low downpayment loans: The costs of public subsidy. Regional Science and Urban Economics, 26(3), 263-285.
24. Deng, Y. H., Quigley, J. M., & Van Order, R. (2000). Mortgage terminations, heterogeneity and the exercise of mortgage options. Econometrica, 68(2), 275-307.
25. Derr, R. E. (2000), “Performing Exact Regression with the SAS System”, paper presented at the 25th Annual SAS Users Group International Conference, Cary, North Carolina, 5 April.
26. Epley, D. R., Liano, K., & Haney, R. (1996). Borrower risk signaling using loan-to-value. Journal of Real Estate Research, 11(1), 71-86.
27. Espahibodi, P. (1991). Identification of problem banks and binary choice models. Journal of Banking and Finance, 15(1), 53-71.
28. Fox, J. (1991). Regression diagnostics. Newbury Park, CA : Sage Publications.
29. Grander, M. J., & Mills, D. L. (1989). Evaluating the likelihood of default on delinquent loans. Financial Management, 18(4), 55-63.
30. Herzog, J. P., & Earley, J. S. (1970). Home mortgage delinquency and foreclosure. New York : National Bureau of Economic Research.
31. Hosmer, D. W., & Lemeshow, S. (2000). Applied logistic regression (2nd ed.). New York: John Wiley.
32. Ingram, F. J., & Frazier, E. L. (1982). Alternative multivariate tests in limited dependent variable models: An empirical assessment. Journal of Financial and Quantitative Analysis, 17(2), 227-240.
33. Jennings, D. E. (1986). Judging inference adequacy in logistic regression. Journal of the American Statistical Association, 81(394), 471-476.
34. Jung, A. F. (1962). Terms of conventional mortgage loans on existing houses. Journal of Finance, 17(3), 432-443.
35. Kass, R., Goovaerts, M., Dhaene, J., & Denuit, M. (2001). Modern actuarial risk theory. Boston: Kluwer Academic Publishers.
36. Kau, J. B., & Keenan, D. C. (1999). Patterns of rational default. Regional Science and Urban Economics, 29(6), 765-785.
37. Kwack, S. Y. (2000). An empirical analysis of the factors determining the financial crisis in Asia. Journal of Asian Economics, 11(2), 195-206.
38. Lawal, B. (2003). Categorical data analysis with SAS and SPSS applications. London : Lawrence Erlbaum Associates.
39. Lawrence, E. C., Smith, L. D., & Rhoades, R. (1992). An analysis of default risk in mobile home credit. Journal of Banking and Finance, 16(2), 299-312.
40. Le, C. T. (1998). Applied categorical data analysis. New York: John Wiley.
41. Lo, A. W. (1986). Logit versus discriminant analysis: A specification test and application to corporate bankruptcies. Journal of Econometrics, 31(2), 151-178.new window
42. McCullagh, P., & Nelder, J. A. (1989). Generalized linear models (2nd ed.). London : Chapman Hall.
43. Menard, S. (1995). Applied logistic regression analysis. Thousand Oaks, CA : SAGE Publications.
44. Morton, T. G. (1975). A discriminant function analysis of residential mortgage delinquency and foreclosure. AREUEA Journal, 3(1), 73-90.
45. Myers, R. H., Montgomery, D. C., & Vining, G. G. (2002). Generalized linear models: With applications in engineering and sciences. New York : John Wiley.
46. Neter, J., Kutner, M. H., Nachtsheim, C. J., & Wasserman, W. (1999). Applied linear statistical models. New York: McGraw-Hill.
47. Page, A. N. (1964). The variation of mortgage interest rates. Journal of Business, 37(3), 280-294.
48. Powers, D. A., & Xie, Y. (2000). Statistical methods for categorical data analysis. California : Academic Press.
50. Pregibon, D. (1981). Logistic regression diagnostics. Annals of Statistics, 9(3), 705-724.
51. Raftery, A. E. (1986). Choosing models for cross-classifications (Comment on grusky and hauser). American Sociological Review, 51(1), 145-146.
52. SAS Institute (1999). SAS/ATAT user’s guide (8th ed., Vols. 2). Cary NC: SAS Institute.
53. Schwarz, G. (1978). Estimating the dimensions of a model. Annals of Statistics, 6(2), 461-464.
54. Twisk, J. R. (2003). Applied longitudinal data analysis for epidemiology: A practical guide. Cambridge, United Kindgdom : Cambridge University Press .
55. Upton, G. G. (1992). Fisher’s exact test. Journal of Royal Statistical Society, 155(3), 395-402.new window
56. van Deventer, D., & Kenji, Imai (2003). Credit risk models & the Basel Accords. New York : John Wiley.
57. Vandell, K. D. (1978). Default risk under alternative mortgage instruments. Journal of Finance, 33(5), 1279-1296.
58. Vandell, K. D., & Thibodeau, T. (1985). Estimation of mortgage defaults using disaggregate loan history data. AREUEA Journal, 15(3), 292-317.
59. von Furstenberg, G. M. (1969). Default risk on FHA-insured home mortgages as a function of the terms of financing: A quantitative analysis. Journal of Finance, 24, 459-477.
60. von Furstenberg, G. M., & Green, R. F. (1974). Home mortgage delinquencies: A cohort analysis. Journal of Finance, 29(5), 1545-1548.
61. Walker, G. A. (2002). Common statistical methods for clinical research: With SAS examples (2nd ed.). Cary, NC: SAS Institute.
62. Webb, B. G. (1982). Borrower risk under alternative mortgage instruments. Journal of Finance, 37(1), 169-183.
63. Yang, H. C., Chen, C. Y., Chen, C. W., & Chen, T. H. (in press). Estimation on internal wave reflection in a two-layer fluid system by cumulative logistic regression model. Journal of Marine Science and Technology.

64. Zorn, P. M., & Lea, M. J. (1989). Mortgage borrower repayment behavior: A microeconomic analysis with Canadian adjustable rate mortgage data. AREUEA Journal, 17(1), 118-136.
 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
:::
無相關書籍
 
無相關著作
 
無相關點閱
 
QR Code
QRCODE