Geodesic
Dynamics modeling of credit interest rate
Journal of computational and engineering mathematics, Tome 10 (2023) no. 3, pp. 54-66.

Voir la notice de l'article provenant de la source Math-Net.Ru

This article provides statistical modeling of the dynamic changes in the interest rate on loans provided by credit institutions to individuals by districts of the Russian Federation from January 2019 to March 2023, using technical analysis tools. A forecast of the credit interest rate for the Ural Federal District until the end of 2023 was constructed. The influence of external factors on the credit interest rate was studied, such external factors include the key rate of the Central Bank, the percentage of inflation, deposits of individuals, the average monthly nominal accrued wages of employees and the consumer price index for goods and services for the period from January 2019 to March 2023 based on data from the Federal Statistics Service.
Keywords: statistics, modeling, credit interest rate, prediction. 
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     author = {E. K. Zerkina and E. I. Nazarova},
     title = {Dynamics modeling of credit interest rate},
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     pages = {54--66},
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     number = {3},
     year = {2023},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/JCEM_2023_10_3_a4/}
}
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E. K. Zerkina; E. I. Nazarova. Dynamics modeling of credit interest rate. Journal of computational and engineering mathematics, Tome 10 (2023) no. 3, pp. 54-66. http://geodesic.mathdoc.fr/item/JCEM_2023_10_3_a4/