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

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

《財務金融學刊》 16卷1期 (2008/03) Pp. 99-129

https://doi.org/10.6545/JFS.2008.16(1).4

摘要

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。

關鍵字

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

並列摘要

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).

並列關鍵字

hazard function ； maximum likelihood method ； power function ； survivor function ； type I error rate ； type II error rate

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