A dinamic method for risks evaluation in the financial management system
The main definitions and formalization of various types of survival models such as empirical survival function, generalized linear model, Cox proportional hazards model and its modifications and nonparametric models are presented for risk assessment. A dynamic method of risk assessment that allows t...
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Інститут проблем реєстрації інформації НАН України
2019
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drspiprikievua-article-1837242019-12-10T12:10:30Z A dinamic method for risks evaluation in the financial management system Динамічний метод оцінювання ризиків у системі фінансового менеджменту Kuznietsova, N. V. динамічний метод фінансові ризики моделі виживання модель пропорційних ризиків Кокса оцінка Каплан-Майєра dynamic method financial risks survival models Cox proportional hazards model Kaplan-Meier estimation The main definitions and formalization of various types of survival models such as empirical survival function, generalized linear model, Cox proportional hazards model and its modifications and nonparametric models are presented for risk assessment. A dynamic method of risk assessment that allows to assess the risk’s degree and level and also to predict the transition from critical to catastrophic risk by using of parametric, semi-parametric and nonparametric models based on survival functions has been proposed. The method allows to apply data stratification and separately to simulate different survival functions for different data categories. The method involves the identification of statistically significant characteristics, the development of different survival models and selection of the best model by the set of criteria, testing the hypothesis about the same distribution of risk functions and at finally defined time, the probability of risk occurrence or probable losses are determined accordingly. Also it includes two developed by author algorithms that allow prediction of such a time based on the established permissible (critical) probability of risk occurrence or restriction of possible economic losses, in particular, the moment of risk transition from permissible to critical or catastrophic (in the defined amount of critical or catastrophic losses). The algorithm for calculating the moment of transition to the higher risk probability (risk degree) could be presented in two possible variations. The first possibility is defining time through the calculation of the derivative of the risk function, which was given explicitly. The second option is to define through the «probability reserve» (as the speed of probability change). The algorithm for determining the moment of occurrence of risk’s critical (catastrophic) level by losses is performed as an iterative step-by-step procedure of transition point search for losses from critical to catastrophic. Tabl.: 1. Fig.: 1. Refs: 12 titles. Наведено основні визначення та формалізацію різних типів моделей виживання для оцінювання ризиків, зокрема, на основі пропорційних ризиків Кокса та їхньої модифікації, лінійних і непараметричних моделей. Запропоновано динамічний метод оцінювання ризиків, який дозволяє оцінити ступінь і рівень ризику та спрогнозувати момент переходу ризику з критичного до катастрофічного із використанням параметричних, напівпараметричних і непараметричних моделей на основі функцій виживання. Метод дозволяє застосовувати стратифікацію даних та окремо здійснювати моделювання різними функціями виживання для різних категорій даних. Автором розроблено два алгоритми, що дозволяють спрогнозувати такий момент часу на основі встановленої допустимої (критичної) імовірності настання ризику або обмеження щодо можливих економічних втрат, зокрема, момент переходу ризику від допустимого до критичного або катастрофіч-ного (за визначеним обсягом критичних або катастрофічних втрат). Інститут проблем реєстрації інформації НАН України 2019-11-21 Article Article application/pdf http://drsp.ipri.kiev.ua/article/view/183724 10.35681/1560-9189.2019.21.3.183724 Data Recording, Storage & Processing; Vol. 21 No. 3 (2019); 85-98 Регистрация, хранение и обработка данных; Том 21 № 3 (2019); 85-98 Реєстрація, зберігання і обробка даних; Том 21 № 3 (2019); 85-98 1560-9189 uk http://drsp.ipri.kiev.ua/article/view/183724/184159 Авторське право (c) 2021 Реєстрація, зберігання і обробка даних |
| institution |
Data Recording, Storage & Processing |
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| datestamp_date |
2019-12-10T12:10:30Z |
| collection |
OJS |
| language |
Ukrainian |
| topic |
dynamic method financial risks survival models Cox proportional hazards model Kaplan-Meier estimation |
| spellingShingle |
dynamic method financial risks survival models Cox proportional hazards model Kaplan-Meier estimation Kuznietsova, N. V. A dinamic method for risks evaluation in the financial management system |
| topic_facet |
динамічний метод фінансові ризики моделі виживання модель пропорційних ризиків Кокса оцінка Каплан-Майєра dynamic method financial risks survival models Cox proportional hazards model Kaplan-Meier estimation |
| format |
Article |
| author |
Kuznietsova, N. V. |
| author_facet |
Kuznietsova, N. V. |
| author_sort |
Kuznietsova, N. V. |
| title |
A dinamic method for risks evaluation in the financial management system |
| title_short |
A dinamic method for risks evaluation in the financial management system |
| title_full |
A dinamic method for risks evaluation in the financial management system |
| title_fullStr |
A dinamic method for risks evaluation in the financial management system |
| title_full_unstemmed |
A dinamic method for risks evaluation in the financial management system |
| title_sort |
dinamic method for risks evaluation in the financial management system |
| title_alt |
Динамічний метод оцінювання ризиків у системі фінансового менеджменту |
| description |
The main definitions and formalization of various types of survival models such as empirical survival function, generalized linear model, Cox proportional hazards model and its modifications and nonparametric models are presented for risk assessment. A dynamic method of risk assessment that allows to assess the risk’s degree and level and also to predict the transition from critical to catastrophic risk by using of parametric, semi-parametric and nonparametric models based on survival functions has been proposed. The method allows to apply data stratification and separately to simulate different survival functions for different data categories. The method involves the identification of statistically significant characteristics, the development of different survival models and selection of the best model by the set of criteria, testing the hypothesis about the same distribution of risk functions and at finally defined time, the probability of risk occurrence or probable losses are determined accordingly. Also it includes two developed by author algorithms that allow prediction of such a time based on the established permissible (critical) probability of risk occurrence or restriction of possible economic losses, in particular, the moment of risk transition from permissible to critical or catastrophic (in the defined amount of critical or catastrophic losses). The algorithm for calculating the moment of transition to the higher risk probability (risk degree) could be presented in two possible variations. The first possibility is defining time through the calculation of the derivative of the risk function, which was given explicitly. The second option is to define through the «probability reserve» (as the speed of probability change). The algorithm for determining the moment of occurrence of risk’s critical (catastrophic) level by losses is performed as an iterative step-by-step procedure of transition point search for losses from critical to catastrophic. Tabl.: 1. Fig.: 1. Refs: 12 titles. |
| publisher |
Інститут проблем реєстрації інформації НАН України |
| publishDate |
2019 |
| url |
http://drsp.ipri.kiev.ua/article/view/183724 |
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AT kuznietsovanv adinamicmethodforrisksevaluationinthefinancialmanagementsystem AT kuznietsovanv dinamíčnijmetodocínûvannârizikívusistemífínansovogomenedžmentu AT kuznietsovanv dinamicmethodforrisksevaluationinthefinancialmanagementsystem |
| first_indexed |
2025-07-17T10:57:45Z |
| last_indexed |
2025-07-17T10:57:45Z |
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1837891443746668544 |