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  • Статистическая модель для оценки формирования климатогенных угроз по данным мониторинга климата
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News
June 4, 2026
Machine Learning Models Can Help Reduce Volatility and Boost Stock Market Returns
The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.
June 3, 2026
Pocket Money, Personal Interest, and Family Practices: What Shapes Students Economic Literacy?
University students' economic literacy depends not only on their field of study but also on their interest in economics, the learning environment, and family financial practices. For example, students who received pocket money irregularly tend to perform better on economic literacy tests than their peers who received financial support on a regular basis. These findings come from a study conducted by HSE University involving more than 1,100 students from five Russian universities. The findings have been published in Cakrawala Pendidikan.
June 3, 2026
Creative Work as a Remedy for Burnout
The creative, supportive atmosphere and innovative methods at the Centre for Sociocultural Research make it appealing to early-career scholars. Over years of working at HSE University, they grow into researchers and lecturers recognised both in Russia and abroad. Chief Research Fellow Zarina Lepshokova and Leading Research Fellow Ekaterina Bushina spoke about their journey at the centre and at HSE, their research, and the role of mentors in their academic success.

 

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Статистическая модель для оценки формирования климатогенных угроз по данным мониторинга климата

Метеорология и гидрология. 2020. № 5. С. 59–65.
Semenov S., Попов И. О., Ясюкевич В. В.

A statistical model for the formation of climate-related hazards is proposed. The formation is described by several meteorological variables or applied climatic indices characterizing a calendar year. Their values or data for their calculation are provided by climate monitoring systems. A climate- related hazard arises when these variables or applied climatic indices together go beyond their safe ranges over substantial number of several consecutive years. Respective minimum values for the number of such years are substantiated for different levels of the likelihood of occurrence of a climate-related hazard. The developed methodology was applied to obtain probabilistic estimates of the climatic range of the tick Ixodes ricinus (Linnaeus, 1758), a vector of dangerous human diseases, and its changes in 2001-2010 as compared to 1971-1980. The results are presented in the form of schematic maps.

Language: Russian
Text on another site
Keywords: изменение климатаоценкаmappingclimate change IXODES RICINUSCLIMATE-RELATED HAZARD STATISTICAL MODEL ASSESSMENT EXAMPLECLIMATIC RANGEКЛИМАТОГЕННАЯ УГРОЗАКАРТОГРАФИЧЕСКОЕ ОТОБРАЖЕНИЕКЛИМАТИЧЕСКИЙ АРЕАЛ СТАТИСТИЧЕСКАЯ МОДЕЛЬ
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