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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/30869


    Title: 台灣股市中下市公司之預測–歷史事件研究法
    Authors: 蘇凡晴
    Contributors: 江振東
    郭維裕


    蘇凡晴
    Keywords: 歷史事件研究法
    Cox迴歸模型
    Logit模型
    上市公司
    下市公司
    Event history analysis
    Cox regression model
    Logit model
    Listed firms
    Delisted firms
    Date: 2002
    Issue Date: 2009-09-14
    Abstract: 本論文主要目地是在研究財務比率對上市公司發生下市事件之預測。我們運用歷史事件研究法和Cox迴歸模型去研究上市公司發生下市事件之原因。同時，我們也針對Cox迴歸模型和Logit模型在發現對下市事件有顯著影響的財務比率作比較。
    This study applies the event history analysis and the Cox regression model to examine the causes of firm delisting, and also compares the performance of the Cox regression model with that of the logit model in detecting factors that have a statistically significant impact on the delisting event. The empirical results show that the hazard rate of firm delisting increases with the ratio of current liabilities to current assets, a binary variable indicating if the total liabilities of a firm is greater than its total assets, and a binary variable indicating if the net income of a firm was negative for the last two quarters, while the hazard rate of firm delisting decreases with increases in the firm size and the ratio of funds provided by operations to total liabilities.
    Reference: 1. Allison, P. D. (1995), Survival Analysis Using the SAS System: A Practical Guide, Cary, NC: SAS Institute, Inc.
    2. Allison, P. D. (1999), Logistic Regression Using the SAS System: Theory and Application, Cary, NC: SAS Institute, Inc.
    3. Andersen, P. K. and R. D. Gill (1982), “Cox’s Regression Model for Counting Processes: A Large Sample Study,” The Annals of Statistics, 10(4), 1100-1120.
    4. Altman, E. I. and R. A. Eisenbeis (1978), “Financial Applications of Discriminant Analysis: A Clarification,” Journal of Financial and Quantitative Analysis, 185-195.
    5. Cox, D. R. (1972), “Regression Models and Life-Tables,” Journal of the Royal Statistical Society, B34 (2), 187-220.
    6. Eisenbeis, R. A. (1977), “Pitfalls in the Application of Discriminant Analysis in Business, Finance, and Economics,” Journal of Finance, 32(3), 875-900.
    7. Grambsch, P. M. and T. M. Therneau (1994), “Proportional Hazards Tests and Diagnostics Based on Weighted Residuals,” Biometrika, 81, 3, 515-526.
    8. Hill, N. T., S. E. Perry, and S. Andes (1996), “Evaluating Firms in Financial Distress: An Event History Analysis,” Journal of Applied Business Research, 12(3), 60-71.
    9. Kalbfleisch, J. D. and R. L. Prentice (1980), The Statistical Analysis of Failure Time Data, New York: John Wiley and Sons.
    10. Kim, Y., D. R. Anderson, T. L. Amburgey, and J. C. Hickman (1995), “The Use of Event History Analysis to Examine Insurer Insolvencies,” Journal of Risk and Insurance, 62(1), 94-110.
    11. Lane, W. R., S. W. Looney, and J. W. Wansley (1986), “An Application of the Cox Proportional Hazards Model to Bank Failure,” Journal of Banking and Finance, 10(4), 511-531.
    12. Lin, D. Y. (1991), “Goodness-of-fit Analysis for the Cox Regression Model Based on a Class of Parameter Estimators,” Journal of the American Statistical Association, 86, 725-728.
    13. Ohlson, J. A. (1980), “Financial Ratios and the Probabilistic Prediction of Bankruptcy,” Journal of Accounting Research, 18(1), 109-131.
    14. Teachman, T. D. and M. D. Hayward (1993), “Interpreting Hazard Rate Models,” Sociological Methods and Research, 21(3), 340-371.
    15. Wheelock, D. C. and P. W. Wilson (1995), “Explaining Bank Failures: Deposit Insurance, Regulation, and Efficiency,” The Review of Economics and Statistics, 77(4), 689-700.
    Description: 碩士
    國立政治大學
    統計研究所
    88354022
    91
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0088354022
    Data Type: thesis
    Appears in Collections:[Department of Statistics] Theses

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