Abstract
In this paper we articulate the idea of utilizing Artificial Immune System (AIS) for the prediction of bankruptcy of companies. Our proposed AIS model considers the financial ratios as input parameters. The novelty of our algorithms is their hybrid nature, where we use modified Negative Selection, Positive Selection and the Clonal Selection Algorithms adopted from Human Immune System. Finally we compare our proposed models with a few existing statistical and mathematical sickness prediction methods.
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References
Altman, E.I.: Financial Ratios, Discriminant Analysis and Prediction of Corporate Bankruptcy. Journal of Finance 23, 189–209 (1968)
Altman, E.I., Haldeman, R.G., Narayanan, P.: ZETATM Analysis: A New Model to identify Bankruptcy Risk of Corporations. Journal of Banking and Finance 1, 29–54 (1977)
Altman, E.I., Hatzell, J., Peck, M.: Emerging Markets Corporate Bonds: A Scoring System. Salomon Brothers, New York, USA (1997)
Brabazon, A., O’Neill, M.: Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series). Springer, New York (2006)
Boggess, L., Hamaker, J.S.: Non-Euclidean Distance Measures in AIRS, an Artificial Immune Classification System. Proceedings of the IEEE Congress on Evolutionary Computation 1, 1067–1073 (2004)
Caouette, J.B., Altman, E.I., Narayanan, P.: Managing credit risk. Wiley Frontiers in Finance. John Wiley & sons Inc., New York (1998)
de Castro, L.N., Timmis, J.: Artificial Immune Systems: A New Computational Intelligence Approach. Springer, London (2002)
de Castro, L.N., von Zuben, F.J.: The Clonal Selection Algorithm with Engineering Applications. In: Proceedings of GECCO 2000, pp. 36–37 (2000)
Forrest, S., Perelson, A.S., Allen, L., Cherukuri, R.: Self-Nonself Discrimination in a Computer. In: Proceedings of the IEEE Symposium on Research in Security and Privacy, pp. 202–212. IEEE Computer Society Press, Los Alamitos, CA (1994)
Griffin, J.M., Lemmon, M.L.: Book to Market Equity, Distress Risk and Stock Returns. Journal of Finance 57, 2317–2336 (2002)
Gupta, L.C.: Financial Ratios for Monitoring Corporate Sickness: Towards a More Systematic Approach. Oxford University Press, Delhi (1983)
Matzinger, P.: Tolerance, Danger, and the Extended Family. Annual Reviews of Immunology 12, 991–1045 (1994)
Matzinger, P.: An Innate Sense of Danger. Seminars in Immunology 10, 399–415 (1998)
Ohlson, J.: Financial Ratios and the Probabilistic Prediction of Bankruptcy. Journal of Accounting Research 18, 109–131 (1980)
Zavgren, C.V.: The Prediction of Corporate Failure, the State of the Art. Journal of Accounting Literature 2, 1–33 (1983)
Zmijewski, M.E.: Methodological Issues Related to the Estimation of Financial Distress Prediction Models. Journal of Accounting Research 22, 59–82 (1984)
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Singh, R., Sengupta, R.N. (2007). Bankruptcy Prediction Using Artificial Immune Systems. In: de Castro, L.N., Von Zuben, F.J., Knidel, H. (eds) Artificial Immune Systems. ICARIS 2007. Lecture Notes in Computer Science, vol 4628. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73922-7_12
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DOI: https://doi.org/10.1007/978-3-540-73922-7_12
Publisher Name: Springer, Berlin, Heidelberg
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