The purpose of this article is to analyze the impact of corporate governance and disclosure policy on corporate financial performance by examining the combined effect of board characteristics and disclosure level on f...The purpose of this article is to analyze the impact of corporate governance and disclosure policy on corporate financial performance by examining the combined effect of board characteristics and disclosure level on financing costs. The empirical analysis, conducted on a sample of 192 Canadian companies, generally shows the importance of board characteristics in determining the level of disclosure and firms＇ costs of financing. In particular, the results found indicate that boards whose characteristics meet the governance requirements that are associated with greater transparency in disclosure on governance attributes reduce the costs of financing of their companies by debt as well as by equity capital.展开更多
This paper presents an in-depth analysis of financially distressed listed companies in China between 1998 and 2002. We compare the predictive power of multiple discriminant analysis （MDA）, logistic regression, and n...This paper presents an in-depth analysis of financially distressed listed companies in China between 1998 and 2002. We compare the predictive power of multiple discriminant analysis （MDA）, logistic regression, and neural network models. We design and implement 126 different forecasting models using different predictive methods, different sample proportions, and different initial independent variables. The aim is to determine which model（s） and variables are best applicable for the short-term prediction of financial distress in China. We find that logistic regression models are superior to multiple discriminant analysis models in terms of prediction accuracy rate, restriction of sample distribution or prediction cost, but the neural network models show promise in their low Type I and Type II errors. The paper also inherently tests the applicability of variables traditionally used for bankruptcy prediction to the purpose of financial distress prediction in China.展开更多
文摘The purpose of this article is to analyze the impact of corporate governance and disclosure policy on corporate financial performance by examining the combined effect of board characteristics and disclosure level on financing costs. The empirical analysis, conducted on a sample of 192 Canadian companies, generally shows the importance of board characteristics in determining the level of disclosure and firms＇ costs of financing. In particular, the results found indicate that boards whose characteristics meet the governance requirements that are associated with greater transparency in disclosure on governance attributes reduce the costs of financing of their companies by debt as well as by equity capital.
文摘This paper presents an in-depth analysis of financially distressed listed companies in China between 1998 and 2002. We compare the predictive power of multiple discriminant analysis （MDA）, logistic regression, and neural network models. We design and implement 126 different forecasting models using different predictive methods, different sample proportions, and different initial independent variables. The aim is to determine which model（s） and variables are best applicable for the short-term prediction of financial distress in China. We find that logistic regression models are superior to multiple discriminant analysis models in terms of prediction accuracy rate, restriction of sample distribution or prediction cost, but the neural network models show promise in their low Type I and Type II errors. The paper also inherently tests the applicability of variables traditionally used for bankruptcy prediction to the purpose of financial distress prediction in China.
