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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.
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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.
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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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Review of regional maternity capital programmes in Russia 2011–2023

Population and Economics. 2024. Vol. 8. No. 2. P. 114–132.
Vakulenko E., Vasileva U., Fadina E.

The article analyzes regional maternity capital programs in 85 regions of the Russian Federation. Their differences in the volume of payments and conditions are examined both spatially and temporally for the period from 2011 to 2023. For analysis, the authors collected a unified information database of existing regional maternity capital programs, which is posted for public access on the Internet. Interactive maps and cards with information about the programs have been prepared. An analysis of the differences and typology of regional maternity capital programs aimed at the birth of children of various orders was carried out.

Research target: Sociology (including Demography and Anthropology Economics and Management
Language: English
Full text
DOI
Keywords: рождаемостьрегионы Россииregions of Russiatotal fertility rateинтерактивные картыbirth orderregional maternity capital programs interactive mapsрегиональные программы материнского капиталаСКРпорядок рождений
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