在本文中，我們收集國內股票上市公司的產業效應變數 (industry effects; Chava and Jarrow, 2004)、市場導出變數 (market-driven variables; Shumway, 2001)、以及財務比率變數 (financial ratios)，將其應用至離散型模式 (discrete-time model; Allison, 1982)，以建立財務危機模式。我們應用最大概似法 (maximum likelihood method)估計模式的參數值，導出參數估計式的漸近常態分配 (asymptotic normal distribution)。實證研究結果顯示，本文所介紹的離散型財務危機模式(discrete-time financial distress model)，對公司財務危機的預測，比羅吉特模式 (logit model; Ohlson, 1980) 以及機率單位模式 (probit model; Zmijewski, 1984)，有更好的樣本外 (out-of-sample) 預測能力。

In this paper, the discrete-time model (Allison, 1982) is applied to predict financial distress using industry effects (Chava and Jarrow, 2004), market-driven variables (Shumway, 2001), and financial ratios for companies listed in Taiwan Stock Exchange. The maximum likelihood method is employed to estimate the values of parameters of the discrete-time financial distress model. The resulting estimates are analyzed through their asymptotic normal distributions. Empirical studies demonstrate that our strategy developed from the discrete-time financial distress model can yield more accurate out-of-sample forecasts than alternatives based on the logit model of Ohlson (1980) and the probit model of Zmijewski (1984).