A study of financial distress prediction models:considering macroeconomic variables

• Main Authors: Li, Gau-Shu, 李國樞
• Other Authors: Chou, Ray Yeu-Tien
• Format: Others
• Language: en_US
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/33987317265628403690

碩士 === 國立交通大學 === 經營管理研究所 === 98 === In this paper, we use the discrete-time survival model, discrete-time Cox model, Logit model, and Probit model to predict the probability of financial distress for each firm. We use a set of variables, including market-driven variables, accounting ratios, and macroeconomic variables to predict financial distress. Shumway estimates a multi-period Logit model that can be defined as discrete-time survival model. The maximum likelihood method is used to determine the probability of the model. Then we want to modify the discrete-time survival model’s likelihood function because it ignores the probability of surviving at time t for all firms. Empirical studies demonstrate that the dynamic models can yield more accurate out-of-sample forecasts than static models in general. All these macroeconomic variables are significant. Unfortunately, three sets of variables’ type-one-error rate are higher than original sets of variables.