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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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?

Современные представления о стресс-зависимых нарушениях менструального цикла

Акушерство и гинекология. 2016. № 12. С. 34–40.
Ragimova A., Волель Б. А., Кузнецова И. В., Бурчаков Д. И.

Objective. To carry out a systematic analysis of the data available in the literature on the problem of menstrual cycle disorders arising from psychological stress. Material and methods. For the analysis, foreign and Russian papers published in the past 15 years were sought in the international citation system Pubmed. Results. The current theories of the mechanism of psychogenic menstrual irregularities and the features of the latter developing due to psychological stress are described. Conclusion. The data of the studies demonstrating different stress sensitivity and characteristics of the personality structure in women who responded to stress as menstrual dysfunction were analyzed.

Research target: Medical and Health Sciences
Language: Russian
DOI
Text on another site
Keywords: psychiatryпсихиатрияневрологияNeurology
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