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News
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.
October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.
October 6, 2026
International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod Brings Together Scientists from Russia and Serbia
The International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod’ was held at the Nizhny Novgorod House of Scientists from September 23 to 26. The event was organised by HSE University–Nizhny Novgorod and the Nizhny Novgorod House of Scientists, with the participation of Sberbank and the Institute of Physics Belgrade. The symposium was held for the second time: the first conference took place in 2025 and attracted considerable interest from the academic community.

 

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Подходы к оценке дефолтности рейтинговых шкал кредитных рейтинговых агентств

Деньги и кредит. 2024. Т. 83. № 4. С. 98–118.
Ozerov K., Кутенко С. В.

Under limited data, the classical cohort method for the creation of migration matrices does not fully reflect the dynamics of the credit quality of the objects within the sample. This problem is exacerbated for objects of lower credit quality less represented in the sample. This paper investigates a continuous time approach to the creation of migration matrices. A continuous time migration matrix considers migrations between the credit quality of objects on a given horizon on a daily basis, and thus not only the initial state of the default object, but also its movement between credit quality categories up to the moment of default. We demonstrate that the classical cohort method is inferior to the continuous time method both on simulated data and in the analysis of the real migration statistics of the credit ratings of Russian companies. The cohort method overestimates the probability of default across the entire credit rating scale. The continuous time method consistently surpasses the cohort method in accuracy and efficiency starting from the second year of observations and allows the mitigation of the problem of data scarcity.

Research target: Economics and Management Mathematics
Language: Russian
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Keywords: probability of defaultвероятность дефолтаcredit ratingsкредитные рейтингиtransition matrixcredit risk modelsматрица миграциймоделирование кредитного риска
Publication based on the results of:
Decision-Making in Socio-Economic, Political and Financial Spheres (2025)
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