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April 28, 2026
Scientists Develop Algorithm for Accurate Financial Time Series Forecasting
Researchers at the HSE Faculty of Computer Science benchmarked more than 200,000 model configurations for predicting financial asset prices and realised volatility, showing that performance can be improved by filtering out noise at specific frequencies in advance. This technique increased accuracy in 65% of cases. The authors also developed their own algorithm, which achieves accuracy comparable to that of the best models while requiring less computational power. The study has been published in Applied Soft Computing.
April 27, 2026
Fair Division: How Mathematics Helps to Divide the Indivisible
How can items be allocated among participants so that no one feels short-changed? Alexander Karpov, Assistant Professor at the Faculty of Economic Sciences, and his Singaporean colleague, Prof. Warut Suksompong, set out to find a mathematical answer to this question. In this interview, they discuss how a model of rational preferences is constructed, why one cannot rely on a simple sum of values, and where an algorithm that asks a minimal number of questions can be useful.
April 24, 2026
Electronics of the Future: Why Superconductors and Spintronics Work Together
It was once believed that superconductivity and magnetism avoided each other like the devil avoids holy water. However, modern nanostructures prove the opposite. A Russian theoretical physicist and Indian experimentalists have joined forces to create the electronics of the future—free from energy losses. Nataliya Pugach, Professor at the School of Electronic Engineering at HSE MIEM and Leading Research Fellow at the Quantum Nanoelectronics Laboratory, explains how a long-standing acquaintance in Cambridge grew into a mirror laboratory project with the Indian Institute of Technology Bombay (IIT Bombay), how superconducting spintronics works, and what surprises a researcher in India beyond the university campus.

 

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Долгосрочный прогноз компенсаторной миграции в России

Журнал Новой экономической ассоциации. 2023. № 1(58). С. 48–64.
Yumaguzin V., Vinnik M. V.

The population of Russia was declining since 2018 due to the growth of natural loss and the uneven dynamics of net migration, which only partially compensated for it. In the short term, even the most favorable scenario of Russia’s demographic development, which provides for high levels of fertility, life expectancy and migration, leads to a decrease in the population from the current 146.2 to 145.2 million persons in 2026, and only after that point, a growth can be expected. According to the medium and low options, the population will decrease to 137.5 and 84.4 million persons respectively by the end of the century. This makes necessary to calculate a level of the replacement migration, which would compensate the natural decline and maintain the current population of Russia. The cohort- component method was used in forecasting, the population as of 01.01.2021 was taken as the base. Depending on various scenarios of fertility and mortality, the level of annual replacement migration growth in 2021–2023 should correspond to 460–1200 thousand persons, which is 2–6 times higher than suggested by the average, most realistic, migration scenario. The value is also 1.5–4.5 times higher than in high migration scenario. After that, the urgency for replacement migration decreases and from the 2040s, according to the average variant, the net migration will correspond to the upper, optimistic, migration scenario (450–500 thousand persons), which implies a greater probability of achieving it. In 2077, the level of replacement migration intersects with the average scenario of net migration (250 thousand persons), and in the period 2084–2100 corresponds to the lower scenario (60–70 thousand persons). According to the high variant, the level of replacement migration is rapidly decreasing due to a signifi cant increase in fertility and life expectancy and since the late 2030s even in the case of migration decline the population would not shrink. With negative trends of natural movement in the low variant, the level of required replacement migration throughout the forecast period is extremely high and unlikely, 1–1.2 million persons annually, which indicates the impossibility of stabilizing the population in this variant. Higher levels of immigration make possible to recoup the growth of the demographic burden only in the medium term, subsequently, the aging of the arrived contingents of migrants leads to an increase in the demographic burden of the elderly. Thus, to preserve the population, it is necessary to fi nd a balance between relatively easy-to-manage migration fl ows and solving fundamental issues in the fi eld of reducing mortality and creating favorable conditions for the birth of the desired number of children in families.

Research target: Sociology (including Demography and Anthropology Economics and Management
Language: Russian
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Keywords: численность населенияpopulation sizeзамещающая миграцияdemographic burdenдемографическая нагрузкадемографический прогнозdemographic forecastcompensatory migrationreplacement migrationкомпенсаторная миграция
Publication based on the results of:
Spatial measurement of demographic dynamics in Russia: long-term and short-term changes in the diversity of human reproduction regimes, migration and demographic structures of the population at the regional level (2022)
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