Kazakova K.A. MULTIDIMENSIONAL REGRESSIVE MODELING AND FORECASTING OVERDUE CREDIT INDEBTEDNESS

Kazakova Kristina Anatolyevna
Postgraduate Student, Department of World Economy and Finance, Astrakhan State University
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Tatishcheva St., 20a, 414056 Astrakhan, Russian Federation


Abstract. The paper proposes a new approach to formation of bank reserve on possible credit losses. This methodology is considered as an alternative to the traditional approach of Making Provisions for Possible Losses on Loans, Loans and Similar Debts, acting on the territory of the Russian Federation. In the research the econometric models of multiple regression of credit indebtedness from macroeconomic indicators are constructed, dot and interval forecasts of values of credit indebtedness are calculated, and also the necessary reserve volume on a covering of the corresponding credit losses is calculated. At the end of the paper the efficiency of the proposed approach to the system of reserve allocation is estimated and the rationality of its application as a quantitative method of estimating credit risk in the system of modern bank risk management is defined.
Key words: bank reserve, overdue credit indebtedness, macroeconomic indicators, multiple regression, modeling, forecasting.

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MULTIDIMENSIONAL REGRESSIVE MODELING AND FORECASTING OVERDUE CREDIT INDEBTEDNESS by Kazakova Kristina Anatolyevna is licensed under a Creative Commons Attribution 4.0 International License.

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