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September 18, 2026
When Pictures Hinder Understanding: Illustrations May Impede Learning of Abstract Ideas
Illustrations can help remember specific actions but do not always make abstract ideas easier to learn. Researchers from HSE University and Humboldt University compared how people learn from texts with different levels of abstractness. They found that participants remembered illustrations better and performed better on related tasks after reading a multimedia text about yoga asanas than after reading an abstract text about the Nash equilibrium. The findings could help improve the selection of illustrations for educational and informational materials. The study has been published in Learning and Instruction.
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International conflicts, crises and digital overload—the modern world puts our minds to the test every day. Traditional psychology often focuses on the consequences: anxiety, depression, and psychosomatic disorders. But what if we looked at the problem differently—through the lens of the resources that prevent us from breaking down? Psychological immunity is precisely this set of resources. Alena Zolotareva and her group, Psychological Immunity as a Resource for Positive Functioning, are developing an integrative model of this phenomenon, adapting diagnostic tools and preparing for large-scale empirical research. Why do psychologists need to collaborate with medical professionals, and how could their research transform preventive care in clinics and corporations?

 

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Downside Market Risk: A Key Determinant of Cryptocurrency Returns

Экономическая политика. 2025. Т. 20. № 1. С. 30–55.
Kuslyaikin A.

This paper is one of the first studies to investigate how downside market risk affects cryptocurrency returns. Based on weekly data for more than 900 cryptocurrencies from 2014 to 2018, downside market risk is considered in three different forms as it arises in the cryptocurrency market, the aggregate alternative investment market, and the stock market. The empirical part of the study employs regression analysis applied to each of three definitions of market risk. First, individual cryptocurrency betas are obtained with a rolling window approach. Second, factor portfolios are constructed based on individual betas to test factor strategies. Third, cross-sectional analysis is used to estimate risk premiums. The conclusion is that cryptocurrency returns are very sensitive to cryptocurrency market drops and insensitive to the dynamics of other financial assets. Downside market risk has a positive and significant effect on cryptocurrency returns, a result which is valid for both individual-instrument and portfolio investment. However, the effects of downside market risk for cryptocurrencies are not offset by any other risk factors, and the key conclusion to be drawn is that high cryptocurrency returns are fair compensation for elevated downside risk. A three-factor model that incorporates a downside market risk factor along with SMB and WML factors was the most useful of those considered, as it explained more than half of cross-sectional returns and surpassed other established models. These results may be useful for daily cryptocurrency trading as well as for further study of cryptocurrency returns. 

Language: Russian
DOI
Text on another site
Keywords: рыночный рискдиверсификацияdiversificationmarket riskфакторные моделиalternative investmentsальтернативные инвестицииcryptoassetsкриптоактивы Factor models
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