Applying Combined Approach of Sequential Floating Forward Selection and Support Vector Machine to Predict Financial Distress of Listed Companies in Tehran Stock Exchange Market

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FALLAHPOUR SAEID; RAEI REZA; NOROUZIAN LAKVAN EISA

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Journal: FINANCIAL RESEARCH Year:2018 | Volume:20 | Issue:3 Page(s): 289-304

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Title

Applying Combined Approach of Sequential Floating Forward Selection and Support Vector Machine to Predict Financial Distress of Listed Companies in Tehran Stock Exchange Market

Author(s)

FALLAHPOUR SAEID | RAEI REZA | NOROUZIAN LAKVAN EISA | Issue Writer Certificate

Keywords

Feature selectionQ1

Sequential floating forward selectionQ1

WrapperQ2

Financial distressQ1

Hybrid modelsQ2

Abstract

Objective: Nowadays, Financial distress prediction is one of the most important research issues in the field of risk management that has always been interesting to banks, companies, corporations, managers and investors. The main objective of this study is to develop a high performance predictive model and to compare the results with other commonly used models in Financial distress prediction Methods: For this purpose, Sequential floating forward selection that is considered as the generalized form of sequential forward selection method and as one of the Wrapper methods, and sequential forward selection method in combination with support vector machine were used. These models are combined models of Feature selection and classifier. Logistic regression model which is a statistical classification models, has also been used in the present study. Results: After reviewing the important financial ratios, 29 financial ratios that were mostly used in previous researches were chosen. Paired T-test results showed that with a 95% confidence level. The proposed model provides higher accuracy than other models used in this study. Conclusion: Results showed that the proposed model of this research has significantly better performance in predicting Financial distress than the sequential forward selection method and Logistic regression model in one year, two years and three years before Financial distress.

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APA: Copy

FALLAHPOUR, SAEID, RAEI, REZA, & NOROUZIAN LAKVAN, EISA. (2018). Applying Combined Approach of Sequential Floating Forward Selection and Support Vector Machine to Predict Financial Distress of Listed Companies in Tehran Stock Exchange Market. FINANCIAL RESEARCH, 20(3 ), 289-304. SID. https://sid.ir/paper/91211/en

Vancouver: Copy

FALLAHPOUR SAEID, RAEI REZA, NOROUZIAN LAKVAN EISA. Applying Combined Approach of Sequential Floating Forward Selection and Support Vector Machine to Predict Financial Distress of Listed Companies in Tehran Stock Exchange Market. FINANCIAL RESEARCH[Internet]. 2018;20(3 ):289-304. Available from: https://sid.ir/paper/91211/en

IEEE: Copy

SAEID FALLAHPOUR, REZA RAEI, and EISA NOROUZIAN LAKVAN, “Applying Combined Approach of Sequential Floating Forward Selection and Support Vector Machine to Predict Financial Distress of Listed Companies in Tehran Stock Exchange Market,” FINANCIAL RESEARCH, vol. 20, no. 3 , pp. 289–304, 2018, [Online]. Available: https://sid.ir/paper/91211/en

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