Research on Credit Evaluation of Listed Companies in Science and Technology Sector Based on SVM

Su-juan Xu and Mu Zhang ()
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Su-juan Xu: Guizhou University of Finance and Economics, School of Big Data Application and Economics
Mu Zhang: Guizhou University of Finance and Economics, School of Big Data Application and Economics

A chapter in Proceedings of the 10th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2022), 2023, pp 156-162 from Springer

Abstract: ABSTRACT In recent years, the state has strongly supported the development of scientific and technological enterprises. Scientific and technological enterprises occupy an increasingly important position in China's economic development. However, scientific and technological enterprises are in the growth period, and there are many risks in the process of development and expansion, so there are some problems in financing. Based on the establishment of the credit evaluation index system of listed companies in the science and technology sector, this paper calculates the IV value of each index to screen the indicators, and uses SVM to classify the selected sample enterprises, and compares the classification accuracy of the samples before and after the index screening. The results show that the classification accuracy of both training samples and test samples is improved after removing the indicators with little information value, which also shows the feasibility and effectiveness of the model.

Keywords: Science and Technology Enterprises; Support Vector Machine; Credit Evaluation (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-194-4_22

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DOI: 10.2991/978-94-6463-194-4_22

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