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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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?

End of Publication? Open access and a new scholarly communication technology

2016.
Parinov S.
At this time, developers of research information systems are experimenting with new tools for research outputs usage that can expand the open access to research. These tools allow researchers to record research as annotations, nanopublications or other micro research outputs and link them by scientific relationships. If these micro outputs and relationships are shared by their creators publicly, these actions can initiate direct scholarly communication between the creators and the authors of the used research outputs. Such direct communication takes place while researchers are manipulating and organising their research results, e.g. as manuscripts. Thus, researchers come to communication before the manuscripts become traditional publications. In this paper, we discuss how this pre-publication communication can affect existing research practice. It can have important consequences for the research community like the end of publication as a communication instrument, the higher level of transparency in research, changes for the Open Access movement, academic publishers, peer-reviewing and research assessment systems. We analyse a background that exists in the economics discipline for experiments with the pre-publication communication. We propose a set of experiments with already existed and new tools, which can help with exploring the end of publication possible impacts on the research community.
Research target: Media and Communications
Priority areas: business informatics
Language: English
Text on another site
Keywords: Open Accessscholarly communicationpre-publication communicationresearch information systemresearch output usage
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