Research and development theory methods and models for forecasting time series with insurance increments
The most actively developing area of the Russian economy is insurance. 213 insurance companies practicing in Russia have permission to provide insurance services for 2019. A clear-cut ascendancy in insurance premiums, which is proportional to inflation in the country, is an indicator of the increasi...
| Main Authors: | , |
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| Format: | Article |
| Language: | Russian |
| Published: |
Maykop State Technological University
2019-12-01
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| Series: | Новые технологии |
| Subjects: | |
| Online Access: | https://newtechology.mkgtu.ru/jour/article/view/307 |
| _version_ | 1826573215863930880 |
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| author | K. A. Kovaleva I. M. Yakhontova |
| author_facet | K. A. Kovaleva I. M. Yakhontova |
| author_sort | K. A. Kovaleva |
| collection | DOAJ |
| description | The most actively developing area of the Russian economy is insurance. 213 insurance companies practicing in Russia have permission to provide insurance services for 2019. A clear-cut ascendancy in insurance premiums, which is proportional to inflation in the country, is an indicator of the increasing role of insurance in the market economy of the Russian Federation.The article presents classic models for forecasting insurance time series, which obey normal laws, based on mathematical and instrumental methods, and on observations of the components of the predicted time series. The presented time series, possessing a long-term memory, is an exception to the rule.The need to develop methods and models for forecasting time series of insurance with increments, as well as for their forecasting, is an urgent topic, since the lack of specific methods and models still creates problems for predicting incremental time series. In practice, classical forecasting methods give good results, thereby showing the necessity of using linear paradigm methods. As follows, the use of both a linear paradigm and a nonlinear paradigm is relevant, which gives us the opportunity to use them in a mixed form. |
| first_indexed | 2024-03-10T07:01:35Z |
| format | Article |
| id | doaj.art-1bab267cd4d0496ab6c693e38dd95773 |
| institution | Directory Open Access Journal |
| issn | 2072-0920 2713-0029 |
| language | Russian |
| last_indexed | 2025-03-14T12:39:22Z |
| publishDate | 2019-12-01 |
| publisher | Maykop State Technological University |
| record_format | Article |
| series | Новые технологии |
| spelling | doaj.art-1bab267cd4d0496ab6c693e38dd957732025-03-02T09:11:29ZrusMaykop State Technological UniversityНовые технологии2072-09202713-00292019-12-010423924810.24411/2072-0920-2019-10424305Research and development theory methods and models for forecasting time series with insurance incrementsK. A. Kovaleva0I. M. Yakhontova1FSBEI of HE «Kuban State Agrarian University named after I.T. Trubilin»FSBEI of HE «Kuban State Agrarian University named after I.T. Trubilin»The most actively developing area of the Russian economy is insurance. 213 insurance companies practicing in Russia have permission to provide insurance services for 2019. A clear-cut ascendancy in insurance premiums, which is proportional to inflation in the country, is an indicator of the increasing role of insurance in the market economy of the Russian Federation.The article presents classic models for forecasting insurance time series, which obey normal laws, based on mathematical and instrumental methods, and on observations of the components of the predicted time series. The presented time series, possessing a long-term memory, is an exception to the rule.The need to develop methods and models for forecasting time series of insurance with increments, as well as for their forecasting, is an urgent topic, since the lack of specific methods and models still creates problems for predicting incremental time series. In practice, classical forecasting methods give good results, thereby showing the necessity of using linear paradigm methods. As follows, the use of both a linear paradigm and a nonlinear paradigm is relevant, which gives us the opportunity to use them in a mixed form.https://newtechology.mkgtu.ru/jour/article/view/307forecastingincremental time seriesmathematical and instrumental methodsinformation technologyphase trajectoriesfractal analysislinear programminginsurance |
| spellingShingle | K. A. Kovaleva I. M. Yakhontova Research and development theory methods and models for forecasting time series with insurance increments Новые технологии forecasting incremental time series mathematical and instrumental methods information technology phase trajectories fractal analysis linear programming insurance |
| title | Research and development theory methods and models for forecasting time series with insurance increments |
| title_full | Research and development theory methods and models for forecasting time series with insurance increments |
| title_fullStr | Research and development theory methods and models for forecasting time series with insurance increments |
| title_full_unstemmed | Research and development theory methods and models for forecasting time series with insurance increments |
| title_short | Research and development theory methods and models for forecasting time series with insurance increments |
| title_sort | research and development theory methods and models for forecasting time series with insurance increments |
| topic | forecasting incremental time series mathematical and instrumental methods information technology phase trajectories fractal analysis linear programming insurance |
| url | https://newtechology.mkgtu.ru/jour/article/view/307 |
| work_keys_str_mv | AT kakovaleva researchanddevelopmenttheorymethodsandmodelsforforecastingtimeserieswithinsuranceincrements AT imyakhontova researchanddevelopmenttheorymethodsandmodelsforforecastingtimeserieswithinsuranceincrements |