Host: The Japan Society for Management Information
Name : Annual Conference of Japan Society for Management Information 2017 Spring
Location : [in Japanese]
Date : March 09, 2017 - March 10, 2017
Critical elements in the process of predicting business failures are selection of financial indicators and construction of a forecast model. Many traditional methods implement these two tasks separately, and do not guarantee the optimality on the whole process. This study uses the AdaBoost algorithm so that these two processes can be realized within a single coherent framework. Setting financial ratios generated from arbitrary two items in the time-series financial data as candidates of indicators, our proposed method selects the effective financial ratios and derives the discrimination function which can predict companies going bankrupt in a few years. Experimental results show that our method can distinguish failed firms from continuing ones with higher accuracy by using the proposed temporal financial ratios.
