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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.
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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Эмпатия: динамика поведения на фоне глобального стресса пандемии COVID-19 в России

Сибирские исторические исследования. 2024. № 2. С. 144–163.
Буркова В. Н., Butovskaya M., Ермаков А. М., Галимханов А. Б., Емельянов А. В., Зинурова Р. И., Калиниченко О. В.

Objective of the study: analysis of the dynamics of empathic behavior,
measured using the Interpersonal Reactivity Index, in Russia during three waves of the COVID-19 pandemic. Analysis of the relationships between empathy, anxiety and
aggression during the pandemic. Research of human behavior during a pandemic
contributes to understanding the best ways to adapt to global stress. Empathy can have
both positive (development of mutual assistance and cooperation during COVID-19)
and negative consequences (risk factor for depression and increased anxiety) for mental
health. The study examined the dynamics of empathy during three waves of the
pandemic in Russia, as well as the relationship between empathy, anxiety and
aggression. The presence and nature of relationships were tested through multivariate
analysis of covariance and regression analysis. The total sample was 7,174 people and
was collected among students from several regions of Russia. Russian-language
versions of questionnaires for empathy by Interpersonal Reactivity Index, for
aggressive behavior by Buss-Perry, and for anxiety Generalized Anxiety Disorder
(GAD-7). A large sample from different regions of Russia during three waves of the
COVID -19 pandemic shows the dynamics of empathic behavior: the minimum level
of empathy was observed during the first wave, then reached its maximum by the
second phase, and began to decline by the third. Significant positive correlations of all
empathy scales with anxiety were also found - more empathic people had higher selfratings
of stress. Associations with aggression are more complex depending on the
empathy scale and the aggression scale. Since the beginning of the pandemic, there has
been an increase in empathy followed by a decrease. There is a relationship between
empathy scales, anxiety levels and aggression scales.

Research target: Sociology (including Demography and Anthropology
Language: Russian
Full text
DOI
Keywords: эмпатияanxietyempathyстрессCOVID-19COVID-19
Publication based on the results of:
Interactions between homoarchical and heterarchical cultures in varying historical contexts (2024)
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