Time Series Model for Bankruptcy Prediction via Adaptive Neuro- Fuzzy Inference System

Bankruptcy prediction has been addressed by many researchers in the field of finance since few decades. One of the best approaches to deal with this issue is considering it as a classification problem. In this paper a time series prediction model of bankruptcy via Adaptive neuro-fuzzy inference system (ANFIS) is formulated, which is capable of predicting the bankruptcy of a firm for any future time. The data used in this study has been extracted from the past financial records of ongoing and failed enterprises. The extracted financial ratios are preprocessed by calculating Altman’s Z-score before feeding into Time series model. The Time series prediction is carried out using ANFIS to predict the bankruptcy at any given time which overcomes the limitation of Altman’s basic model of bankruptcy prediction. Fuzzy Logic Tool box of MATLAB has been exploited for simulations and evaluation of the model. Numerical illustration is provided to demonstrate the efficiency of proposed model.

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