Variable Selection for International Bankruptcy Forecasts
Corporate financial distress not only incurs serious financial loss to its creditors but also has a high cost to the society and the country’s economy.Consequently,financial distress prediction studies are important to all those involved: owners,shareholders,lenders,suppliers,and government.In this paper,we focus on the corporate bankruptcy prediction for international market using CompuStat Global database.First,we introduce a robust variable selection technique,called adaptive lasso (least absolute shrinkage and selection operator),on the global corporate bankruptcy data in search for a parsimonious default forecasting model.Second,we demonstrate a comprehensive case study on Japan bankruptcy prediction.Comparing to US and UK,significant variables selected are generally different across countries.Only firm’s activity indicator Sales/Total Assets displays uniform significance across three countries.
Default Prediction Global Bankruptcy LASSO Model Selection
Shaonan TIAN Yan YU
Department of Marketing and Decision Sciences, College of Business, San Jose State University, San J Department of Business Analytics, Carl H. Lindner College of Business, University of Cincinnati, Cin
国际会议
苏州
英文
103-107
2013-07-08（万方平台首次上网日期，不代表论文的发表时间）