Rating change classication of insurance companies indicators

  • V. P. Zubchenko Taras Shevchenko National University of Kyiv
  • Ye. O. Kostiuk Taras Shevchenko National University of Kyiv
  • M. O. Lukashchuk Taras Shevchenko National University of Kyiv; Instituto Politecnico Nacional, Centrode Investigacionen Computacion, Mexico City, Av. Juan de Dios Batiz S/N, Nueva Industrial Vallejo, Gustavo A. Madero, 07738 Ciudad de Mexico, Mexico
  • A. M. Yaroshevskyi Taras Shevchenko National University of Kyiv


In this paper we investigate the relationship between financial indicators of insurance companies and news space. The news space is considered as a set of topics. The goal of the paper is to fit the model in order to forecast company's rating change for given indicators — whether rating will go up or down regarding the current value. As the data set we use news articles of the relevant insurance topics for the specified time period. The approach we use includes search for the most influential topics for the given indicator. To retrieve topics, we used Latent Dirichlet Allocation (LDA) algorithm and Naive Bayes model. For the validation the Leave-One-Out approach was used with accuracy metric.

Key words: LDA, news space analysis, topic modelling, Naive Bayes, financial indicators of insurance company.

Pages of the article in the issue: 31 - 35

Language of the article: Ukrainian


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How to Cite
Zubchenko, V. P., Kostiuk, Y. O., Lukashchuk, M. O., & Yaroshevskyi, A. M. (1). Rating change classication of insurance companies indicators. Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics, (1-2), 31-35. https://doi.org/10.17721/1812-5409.2020/1-2.4
Algebra, Geometry and Probability Theory