| 研究生: |
陳奕如 Chen, Yi Ru |
|---|---|
| 論文名稱: |
以重複事件分析法分析信用評等 Recurrent Event Analysis of Credit Rating |
| 指導教授: |
謝淑貞
Shieh, Shwu Jane |
| 學位類別: |
碩士
Master |
| 系所名稱: |
商學院 - 國際經營與貿易學系 Department of International Business |
| 論文出版年: | 2008 |
| 畢業學年度: | 96 |
| 語文別: | 英文 |
| 論文頁數: | 39 |
| 中文關鍵詞: | 信用評等 、重複事件分析法 、Cox比例風險模型 |
| 外文關鍵詞: | recurrent event analysis, general class of semiparametric model |
| 相關次數: | 點閱:80 下載:53 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
This thesis surveys the method of extending Cox proportional hazard models (1972) and the general class of semiparametric model (2004) in the upgrades or downgrades of credit ratings by S&P. The two kinds of models can be used to modify the relationship of covariates to a recurrent event data of upgrades or downgrades. The benchmark credit-scoring model with a quintet of financial ratios which is inspired by the Z-Score model is employed. These financial ratios include measures of short-term liquidity, leverage, sales efficiency, historical profitability and productivity. The evidences of empirical results show that the financial ratios of historical profitability, leverage, and sales efficiency are significant factors on the rating transitions of upgrades. For the downgrades data setting, the financial ratios of short-term liquidity, productivity, and leverage are significant factors in the extending Cox models, whereas only the historical profitability is significant in the general class of semiparametric model. The empirical analysis of S&P credit ratings provide evidence supporting that the transitions of credit ratings are related to some determined financial ratios under these new econometrics methods.
Index
Abstract……………………………………………………………………………….1
1. Introduction……………………………………………………………………… ..3
2. Literature Review…………………………………………………………………..6
3. Methodology
3.1 Financial Analysis……………………………………………………………..10
3.2 Econometrics Methodology-Traditional……………………………………….12
3.3 Semiparametric General Class of Model…………………………………… 16
4. Empirical Analysis
4.1 Data……………………………………………………………………………21
4.2 Estimation of Models………………………………………………………….22
4.3 Upgrades………………………………………………………………………23
4.4 Downgrades……………………………………………………………………25
5. Conclusions………………………………………………………………………..27
References…………………………………………………………………………..28
Appendix……………………………………………………………………………..30
1. Altman, E.I., ‘Financial ratios, discriminant analysis and prediction of corporate bankruptcy’, Journal of Finance, vol. 23 (1968), 589-609.
2. Altman, E.I., Rijken, H.A., ‘How rating agencies achieve rating stability’, Journal of Banking & Finance, vol. 28 (2004), 2679-2714.
3. Baker, H.K., Mansi, S.A., ‘Assessing credit rating agencies by bond issuers and institutional investors’, Journal of Business Finance & Accounting, vol. 29 (2002), 1367-1399.
4. Blume, M.E., Lim, F. and Mackinlay, C., ‘The declining credit quality of U.S. corporate debt: Myth or reality?’, Journal of Finance, vol. 53 (1998), 1389-1413.
5. Cox, D.R., ‘Regression models and life-tables’ (with discussion), Journal of the
Royal Statistical Society, Series B, 34 (1972), 187-220.
6. Cox, D.R., ‘Partial Likelihood’, Biometrika (1975), 62, 269-276.
7. Horrigan J.O., ‘The determination of long term credit standing with financial
ratios’, Journal of Accounting Research, Supplement (1966), 44-62.
8. Kaplan, R.S., Urwitz, G., ‘Statistical models on bond ratings: A methodological inquiry’, Journal of business, vol. 52 (1979), 231-261.
9. Peña, E.A., Hollander, M., ‘Models for recurrent events in reliability and survival
analysis’, Soyer, R., Mazzuchi, T., Singpurwalla, N. (Eds.), Mathematical
Reliability: An Expository Perspective. Kluwer Academic Publishers, Dordrecht
(2004), 105-123.
10. Peña, E.A., Slate, E.H., and Gonzalez, J.R., ‘Semiparametric inference for a general class of models for recurrent events’, Journal of Statistical Planning and Inference, vol. 137 (2006), 1727-1747.
11. Pinches, G.E., Mingo, K.A., ‘A multivariate analysis of industrial bond ratings’, Journal of Finance, vol. 28 (1973), 1-18.
12. Pogue, T.F., Soldofsky, R.M., ‘What’s in a bond rating?’, Journal of Financial and Quantitative Analysis, vol. 4 (1969), 201-28.
13. Rondeau, V., Commenges, D., and Joly, P., ‘Maximum penalized likelihood
estimation in a Gamma-Frailty model’, Lifetime Data Analysis, vol. 9 (2003),
139-153.
14. Shin, Y.S., Moore, W.T., ‘Explaining credit rating differences between Japanese and U.S. agencies’, Review of Financial Economics, vol. 12 (2003), 327-344.
15. Therneau, T.M., Grambsch, P.M., ‘Modeling Survival Data: Extending the Cox Model’, Springer, (2000).
16. Wei, L.J., Lin, D.Y., and Weissfeld, L., ‘Regression Analysis of Multivariate
Incomplete Failure Time Data by Modeling Marginal Distributions’, Journal of the
American Statistical Association, vol. 84 (1989), 1065-1073.
17. Wei, L.J., Lin, D.Y., ‘The robust inference for the Cox proportional hazards
model’, Journal of the American Statistical Association, vol. 84 (1989), 1074-1078.