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The mortgage lending as the way of financing of housing construction

Lepekhin I.A. The teacher of chair humanitarian and socio-economic subjects, The branch of the Russian state humanitarian University in Tver ( ilja-lepehin@rambler.ru )

Journal: Finance and credit, #21, 2011

Integrated approach of a problem of progress of housing construction in modern Russian conditions requires for its decision of the system approach, use both domestic, and world experience in this area.
     In the present work the way of financing of housing construction due to the mortgage credits, adjusted in the majority of developed countries is investigated.
     It is drawn a conclusion that in conditions of market economy mortgage lending of housing construction is an optimum financial-credit tool of attraction of money resources on construction of objects of the inhabited real estate.


Hierarchical Copulae in Credit Risk Modeling

Kazakova K.A. Astrakhan State University, Astrakhan, Russian Federation ( kristinakazakova0309@gmail.com )

Knyazev A.G. Astrakhan State University, Astrakhan, Russian Federation ( agkniazev@mail.ru )

Lepekhin O.A. Astrakhan State University, Astrakhan, Russian Federation ( okmb07@yandex.ru )

Journal: Digest Finance, #3, 2017

Importance This research outlines an economic and mathematical model of the overdue loan debt. The model is based on copula functions allowing to simulate a non-Gaussian distribution of financial risks and credit risk, in particular.
Objectives The research models a joint distribution of overdue debt series in order to forecast the credit risk exposure. Relying upon the forecast, we intend to evaluate the efficiency of methods used to make provisions for possible losses and subsequently determine a reasonable approach to accruing the provision.
Methods We examine whether hierarchical copula models can be applied to build the joint distribution of overdue loan debt series in relation to banking institutions. It is considered as the basis for making further estimates of the overdue loan debt.
Results We build and evaluate a multivariate copula model of overdue loan debt with the hierarchical structure. Based on the modeled multivariate correlation, we forecast indicators of the overdue loan debt, which could be used as estimated provisions for credit losses. The estimated provisions turn to be sufficient for covering the real amount of overdue debt, being, in most cases, much less than that indicated in Regulation of the Central Bank of the Russian Federation № 254-П, On Rates of Provisions for Loan Losses.
Conclusions and Relevance The multivariate copula model of the overdue loan debt can underlie effective risk management systems in credit institutions.


Hierarchical copula in credit risk modeling

Kazakova K.A. Astrakhan State University, Astrakhan, Russian Federation ( kristinakazakova0309@gmail.com )

Knyazev A.G. Astrakhan State University, Astrakhan, Russian Federation ( agkniazev@mail.ru )

Lepekhin O.A. Astrakhan State University, Astrakhan, Russian Federation ( okmb07@yandex.ru )

Journal: National interests: priorities and security, #6, 2017

Importance This research outlines an economic and mathematical model of the overdue loan debt. The model is based on copula functions allowing to simulate the non-Gaussian allocation of financial risks and credit risk, in particular.
Objectives The research models the joint allocation of overdue debt series in order to forecast the credit risk exposure. Relying upon the forecasting results, we intend to evaluate the efficiency of methods used to make provisions for possible losses and subsequently determine a reasonable approach to accruing the provision.
Methods We examine whether hierarchical copula models can be applied to build the joint allocation of overdue loan debt series in relation to banking institutions. It is considered as the basis for making further estimates of the overdue loan debt.
Results We build and evaluate a multivariate copula model of overdue loan indebtedness with the hierarchical structure. Based on the modeled multivariate correlation, we forecasted indicators of the overdue loan debt, which could be used as estimated provisions for credit losses. The estimated provisions turn to be sufficient for covering the real amount of overdue debt, being, in most cases, much less that that indicated in Regulation of the Central Bank of the Russian Federation № 254-П On Rates of Provisions for Loan Losses.
Conclusions and Relevance The multivariate copula model of the overdue loan debt can underlie effective risk management systems in credit institutions.


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