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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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The Mental Health Continuum – Short Form: The structure and application for cross-cultural studies – a 38 nation study

Journal of Clinical Psychology. 2018. Vol. 74. No. 6. P. 1034–1052.
Żemojtel-Piotrowska M., Piotrowski J. P., Osin E. N., Cieciuch J., Adams B. G., Ardi R., Baltatescu S., Bogomaz S., Bhomi A. L., Clinton A., de Clunie G. T., Czarna A. Z., Esteves C., Gouveia V., Halik M. H., Hosseini A., Khachatryan N., Kamble S. V., Kawula A., Lun V. M., Ilisko D., Klicperova-Baker M., Liik K., Letovancova E., Cerrato S. M., Michalowski J., Malysheva N., Marganski A., Nikolic M., Park J., Paspalanova E., de Leon P. P., Pék G., Rózycka-Tran J., Samekin A., Shahbaz W., Ha T. T., Tiliouine H., van Hiel A., Vauclair M., Wills-Herrera E., Wlodarczyk A., Yahiiaev I., Maltby J.

Objective: The Mental Health Continuum – Short Form is a brief scale measuring positive human functioning. The study aimed to examine the factor structure and to explore the cross-cultural utility of the MHC-SF using bifactor models and exploratory structural equation modelling (ESEM). Method: Using multigroup confirmatory analysis (MGCFA) we examined the measurement invariance of the MHC-SF in 38 countries (university students, N = 8,066; 61.73% women, mean age 21.55 years). Results: MGCFA supported the cross-cultural replicability of a bifactor structure and a metric level of invariance between student samples. The average proportion of variance explained by the general factor was high (ECV = .66), suggesting that the three aspects of mental health (emotional, social, and psychological well-being) can be treated as a single dimension of well-being. Conclusion: The metric level of invariance offers the possibility of comparing correlates and predictors of positive mental functioning across countries; however, the comparison of the levels of mental health across countries is not possible due to lack of scalar invariance. Our study has preliminary character and could serve as an initial assessment of the structure of the MHC-SF across different cultural settings.  Further studies on general populations are required for extending our findings. 

Research target: Psychology
Language: English
Full text
DOI
Keywords: cross-cultural studymeasurement invarianceMental Health Continuum Short Form
Publication based on the results of:
Personality predictors and developmental trajectories of performance and psychological well-being (final) (2018)
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