Earticle

초록

영어

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.

목차

Abstract
 1. Introduction
 2. ANFIS Overview
 3. Model Formulation
  3.1. Z-Score Calculation on Financial Ratios
  3.2. Time Series Prediction via ANFIS
 4. Experiment and Results
 5. Summary and Conclusion
 References

키워드

저자

• Nidhi Arora [ Ganpat University ]
• Jatinderkumar R. Saini [ Narmada College of Computer Application ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605