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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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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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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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«Ты зачем деньги ешь?»: О ресурсной и нересурсной природе рыбы

Кунсткамера. 2020. № 1 (7). С. 79–86.
Рахманова Л. Я.

What is the difference between “trashy” and valuable species of fi sh? Is it possible to say that the
former become ‘food’ for local people, while the latter become “commodity”? In settlements where sterlet,
muksun and sturgeon are the backbone of many families, the circulation of fi sh between the parties takes on
different forms, the meaning of which can only be understood ad hoc. The drop in catches in the Ob River means
that the importance of fi sh as part of the diet is overshadowed, and fi sh is mainly sold, exchanged and bribed.
Thus, for example, the value of sterlet has been justifi ed in several perspectives: its rarity, taste properties, content
of nutrients and the historical tradition of its consumption by high-ranking offi cials. However, a contradiction
emerges in these justifi cations of the symbolic value of fi sh: how can a person, who hardly ever consumes fi sh
himself, describe its properties and health benefi ts? And, on the other hand, if sterlet is included in his daily diet,
can it still be considered a “royal fi sh”, a unique and high-status product? This article is based on the abovedescribed
“interplay” of practices and justifi cations of the “nature” and value of fi sh.

Research target: Effective Natural Resource Management Other social sciences Sociology (including Demography and Anthropology
Priority areas: sociology humanitarian
Language: Russian
Full text
DOI
Text on another site
Keywords: природопользованиеценностьдарvalueresourcenutritionexchangegiftfoodпищаобменпитаниересурсТомская областьрыбный промыселОбьfishingObTomsk Regionnatural resources management
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