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Методы Оценки Вероятности Дефолта Банков

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  • Пересецкий А.А.

Abstract

Представлены результаты эконометрического анализа дефолтов российских банков в 1997-2003 гг. Основная цель исследования - выяснить, насколько публично доступная информация балансовых отчетов банков может быть использована для прогнозирования дефолтов банков. Показано, что предварительная экспертная кластеризация банков, а также учет макроокружения повышают качество моделей дефолта. Предложены эвристические критерии оценки качества прогнозной силы моделей. С помощью скользящей регрессии анализируются тенденции развития российской банковской системы после кризиса 1998 г.

Suggested Citation

  • Пересецкий А.А., 2007. "Методы Оценки Вероятности Дефолта Банков," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 43(3), июль.
    • Handle: RePEc:scn:cememm:43-3-4
    Note: Москва
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    2. Zhivaikina, A. & Peresetsky, A., 2017. "Russian Bank Credit Ratings and Bank License Withdrawal 2012-2016," Journal of the New Economic Association, New Economic Association, vol. 36(4), pages 49-80.
    3. Maria Bondarenko & Maria Semenova, 2018. "Do High Deposit Interest Rates Signal Bank Default? Evidence from the Russian Retail Deposit Market," HSE Working papers WP BRP 65/FE/2018, National Research University Higher School of Economics.
    4. Peresetsky, A. A., 2011. "What factors drive the Russian banks license withdrawal," MPRA Paper 41507, University Library of Munich, Germany.
    5. Dmitriy, Skrypnik & Marina, Shakleina, 2019. "Counter sanctions and well-being population of Russia: econometric analyses," MPRA Paper 94478, University Library of Munich, Germany.
    6. Denis Shibitov & Mariam Mamedli, 2019. "The finer points of model comparison in machine learning: forecasting based on russian banks’ data," Bank of Russia Working Paper Series wps43, Bank of Russia.
    7. Salnikov, V. & Mogilat, A. & Maslov, I., 2012. "Stress Testing for Russian Real Sector: First Approach," Journal of the New Economic Association, New Economic Association, vol. 16(4), pages 46-70.
    8. Емельянов А.М. & Брюхова О.О., 2015. "Исследование Причин Отзыва Лицензий У Российских Коммерческих Банков В Посткризисный Период (2010-2011)," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 51(3), pages 41-53, июль.
    9. Karminsky, A. & Kostrov, A., 2013. "Modeling the Default Probabilities of Russian Banks: Extended Abillities," Journal of the New Economic Association, New Economic Association, vol. 17(1), pages 64-86.

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