使用離散型倖存模式預測公司財務危機機率

On Prediction of Financial Distress Using the Discrete-time Survival Model

10.6545/JFS.2008.16(1).4

黃瑞卿(Ruey-Ching Hwang)；魏曉琴(Hsiao-Chin Wei)；李昭勝(Jack C. Lee)；李正福(Cheng-Few Lee)

危險函數 ； 最大概似法 ； 檢定力函數 ； 存活函數 ； 型I誤差率 ； 型II誤差率 ； hazard function ； maximum likelihood method ； power function ； survivor function ； type I error rate ； type II error rate

財務金融學刊

16卷1期（2008 / 03 / 31）

99 - 129

繁體中文

本文使用離散型倖存模式（discrete-time survival model; Cox and Oakes, 1984），預測公司發生財務危機的機率。我們以最大概似法（maximum likelihood method）估計模式參數值，導出參數估計式的漸近常態分配（asymptotic normal distribution），進而估計公司在樣本內（in-sample）時間點發生財務危機的機率。藉由此機率估計值，我們找出公司發生財務危機的最適判斷值（optimal cutoff value），建立預警模式，並用以分析反預測台灣股票上市公司發生財務危機的總率。實證研究結果顯示本文所介紹的離散型倖存模式對公司財務危機的預測，比羅吉特模式（Iogit model; Ohlson, 1980）以及機率單位模式（probit model; Zmijewski, 1984），有更好的預測能力。

In this paper, the discrete-time survival model (Cox and Oakes, 1984) is proposed to predict the probability of financial distress for each firm under study. The maximum likelihood method is employed to estimate the values of our model's parameters. The resulting estimates are analyzed by their asymptotic normal distributions, and are used to estimate the in-sample probability of financial distress for each firm under study. Using such estimated probability, a strategy is developed to identify failing firms' and is applied to study the probability of bankruptcy in the future for firms listed in Taiwan Stock Exchange, Empirical studies demonstrate that our strategy developed from the discrete-time survival model can yield more accurate forecasts than the alternative methods based on the logit model in Ohlson (1980) and the probit model in Zmijewski (1984).

1. Altman, E.I.(1968).Financial rations, discriminant analysis, and the predict ion of corporate bankruptcy.Journal of Finance,23,589-609.
2. Begley, J.,J. Ming,S. Watts(1996).Bankruptcy classification errors in the 1980s: An empirical analysis of Altman`s and Ohlson`s models.Review of Accounting Studies,1,267-284.
3. Casella, G.,R.L. Berger(2002).Statistical Inference.California Duxbury:
4. Chava, S.,R.A. Jarrow(2004).Bankruptcy prediction with industry effects.Review of Finance,8,537-569.
5. Cox, D.R.(1972).Regression models and life-tables (with discussion).Journal of Royal Statistical Society Series B,34,187-220.
6. Cox, D.R.,D. Oakes(1984).Analysis of Survival Data.New York:Chapman and Hall.
7. Fan, J.,I. Gijbels(1996).Local Polynomial Modeling and Its Application-Theory and Methodologies.New York:Chapman and Hall.
8. Klein, J.P.,M.L. Moeschberger(1997).Survival Analysis: Techniques for Censored and Truncated Data.New York:Springer.
9. Lancaster, T.(1990).The Econometric Analysis of Transition Data.New York:Cambridge University Press.
10. Lando, D.,T.M. Skodeberg(2002).Analyzing rating transitions and rating drift with continuous observations.Journal of Banking and Finance,26,423-444.
11. Lane, W.R.,SW. Loney,J.W. Wansley(1986).An application of the Cox proportional hazards model to bank failure.Journal of Banking and Finance,10,511-531.
12. Ohlson, J.S.(1980).Financial ratios and the probabilistic prediction of bankruptcy.Journal of Accounting Research,19,109-131.
13. Saunders, A.,L. Allen(2002).Credit Risk Measurement: New Approaches to Value at Risk and Other Paradigms.New York:Wiley.
14. Shumway, T.(2001).Forecasting bankruptcy more accurately: a simple hazard model.Journal of Business,74,101-124.
15. Singer, J.D.,J.B. Willett(1993).It`s about time: using discrete-time survival analysis to study duration and the timing of events.Journal of Educational Statistics,18,155-195.
16. Vassalou, M.,Y. Xing(2004).Default risk in equity returns.Journal of Finance,59,831-868.
17. Wand, M.P.,M.C. Jones(1995).Kernel Smoothing.New York:Chapman and Hall.
18. Zmijewski, M.E.(1984).Methodological issues related to the estimation of financial distress prediction models.Journal of Accounting Research,22,59-82.
19. 楊佳寧、陳漢沖(2003)。存活分析模型於信用風險管理之應用－以台灣上市櫃公司為例。貨幣觀測與信用評等，106-118。

1. 魏裕珍、盧陽正、廖婉茹、張倉耀(2012)。公開新聞之資訊內涵能否增進臺灣企業信用評級慣用指標的預測能力？。台灣金融財務季刊，13(4)，27-53。
2. (2012)。公開新聞之資訊內涵能否增進臺灣企業信用評級慣用指標的預測能力？。台灣金融財務季刊，13(4)，27-53。