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Statistics Application of the Dynamics Socio-Economic Processes: A Case of Russian Insurance Data |
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| รหัสดีโอไอ | |
| Creator | Alfira Kumratova, Elena Popova, Elena Khudyakova, Igor Vasilenko, Victor Saykinov |
| Title | Statistics Application of the Dynamics Socio-Economic Processes: A Case of Russian Insurance Data |
| Contributor | - |
| Publisher | TuEngr Group |
| Publication Year | 2564 |
| Journal Title | International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies |
| Journal Vol. | 12 |
| Journal No. | 3 |
| Page no. | 12A3I: 1-8 |
| Keyword | Statistical indicators, Pre-predictive analysis, R/S analysis, risk criteria, Hurst exponent, Insurance time series, Insurance risk. |
| URL Website | http://TuEngr.com/Vol12_3.html |
| Website title | ITJEMAST V12(3) 2021 @ TuEngr.com |
| ISSN | 2228-9860 |
| Abstract | This article demonstrates the work of the tool for forecasting the dynamics of socio-economic time series, data from insurance companies based on the complex use of both classical and nonlinear statistics. To obtain pre-forecast information about the time series, the authors proposed an analysis of classical statistical coefficients (kurtosis, asymmetry, and variation). Thus, a multi-criteria assessment of the stability of the dynamics of time series is presented. The methods of nonlinear dynamics adapted by the authors are proposed to be used in a multi-criteria (two-criteria) mathematical model. The result of the model's operation is an assessment of the trend stability of the time series. The first criterion reflects the time series's memory depth in the form of a fuzzy set obtained based on the R/S-analysis. The second criterion is the Hurst exponent. A two-criteria approach to assessing the trend stability of time series makes it possible to differentiate them according to the trend stability indicator and select working forecast models. |
