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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.
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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.
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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Transformation of Business Model of Generating Companies in Russian Energy Sector

P. 229–241.
Gorgisheli M., Volkova I., Yakovleva A.

Purpose: The paper aims at creation of an effective business model of global generating companies performing on Russian market and to develop a transformation plan of business for one of these companies.

Design/methodology/approach: The face-to-face interviews with Russian senior management of foreign generating companies were conducted to define the strategic development directions and the key characteristics of target business model. The literature review enables to systematize knowledge about the challenges of both global and Russian energy market and of the energy companies' strategic initiatives. The analysis assisted to incorporate innovative elements into new business model of generating companies and to determine the stages of its transformation, taking one of these companies as an example.

Findings: Generating companies' performance is influenced by Russian energy market institutional features. The key directions for companies' development are to increase the share of generating capacity working on RES and to diversify activities. According to these findings, the target business model was created and the scalable plan of refined business model adaptation in a particular generating company was suggested.

Research/practical implications: The findings of the paper appear in elaboration of the methodological approach towards the transformation of foreign generating companies' business models on Russian market. Strategic vision of market evolution and key characteristics of business acticities will let managers create state-of-the-art business model. Adoption of the model in diverse foreign generating companies accumulates the data about the challenges of this process. This fact might give the ground for future research in this field.

Originality/value: Review of the differencies between foreign generating companies' business model in both global and Russian energy sectors. New business model including renewed elements of Russian generating companies and a plan for business model adaptation.

Language: English
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Keywords: energy sectorbusiness modelgenerating company

In book

Innovation Management, Entrepreneurship, and Sustainability - IMES 2019. Proceedings of the 7th International Conference.
Innovation Management, Entrepreneurship, and Sustainability - IMES 2019. Proceedings of the 7th International Conference.
Prague: Vysoká škola ekonomická v Praze, 2019.
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