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  • Электоральная неопределенность и рынки криптовалют: квантильный и изменяющийся во времени анализ с использованием индикаторов на основе СМИ
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News
November 10, 2026
Physicists Train AI to Optimise Particle Beams in Accelerators
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science and the Budker Institute of Nuclear Physics at the Siberian Branch of the Russian Academy of Sciences have developed RLABC (Reinforcement Learning for Accelerator Beamline Control), a framework that uses reinforcement learning to identify optimal settings for a particle accelerator. In a computer simulation, RLABC optimised the accelerator's parameters to achieve a particle transmission rate of 70%. The study has been published in Computer Physics Communications.
November 9, 2026
'Organ-on-a-Chip Technology Could Eliminate the Need for Animal Testing'
The Laboratory of Molecular Physiology at the HSE Faculty of Biology and Biotechnology investigates how molecular regulators known as microRNAs control gene expression and contribute to the development of diseases, including cancer, viral and inflammatory conditions, and pregnancy complications. At HSE University, researchers develop organ-on-a-chip models: miniature devices containing living cells that mimic the functions of human organs, such as the placenta and intestines. These models help researchers understand how diseases develop and how drugs affect them. HSE News Service spoke with Evgeny Knyazev, Head of the Laboratory.
November 9, 2026
Flattened Terrain Models Underestimate Vehicle-to-Vehicle Communication Outages
Researchers at HSE MIEM have shown that widely used simulators of vehicle-to-vehicle communication significantly overestimate its reliability because they assume flat terrain. When terrain features, bridges, and tunnels are taken into account, the outage rate on a mountain serpentine road rises from 21% to 30%, on an overpass from 20% to 33%, and in a tunnel from 0% to 80%. The results have been published in Future Transportation.

 

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Электоральная неопределенность и рынки криптовалют: квантильный и изменяющийся во времени анализ с использованием индикаторов на основе СМИ

Journal of Applied Economic Research. 2026. Т. 25. № 3. С. 853–878.
Кореневский В. В.

U.S. presidential elections represent a key source of political uncertainty that influences financial market dynamics and investor expectations. However, the impact of presidential elections and related news on cryptocurrency price movements remains underexplored, despite the emergence of select empirical studies on this topic. This study aims to assess the relationship between returns and volatility of major cryptocurrencies and the author-developed electoral uncertainty index, VYTIndex, constructed using titles of video publications by news outlets on the YouTube platform over the period 2015–2025. The index is built in two stages: first, a daily sentiment index is calculated as the difference between the number of positive and negative videos; second, conditional volatility is estimated from its dynamics using a GARCH(1,1) model, interpreted as the level of electoral uncertainty. The paper tests two hypotheses: (1) that upper quantiles of the VYTIndex are associated with increased cryptocurrency volatility and reduced returns, and (2) that this index may serve as a shock transmission channel within a system of the ten largest crypto assets. The analysis employs quantile-on-quantile regression to evaluate dependencies across different quantiles of return and volatility distributions, and a time-varying parameter vector autoregression (TVP-VAR) model to investigate dynamic directional connectedness. Results reveal pronounced nonlinearity and heterogeneity in the impact of VYTIndex: for several altcoins, rises in the upper quantiles of the index coincide with heightened volatility, whereas for Bitcoin and stablecoins the reaction is closer to neutral. Moreover, across most periods, the index acts primarily as a receiver rather than a source of market shocks. The theoretical contribution of this research lies in advancing approaches to measuring political uncertainty as variability of sentiment in the media space and in evaluating the role of electoral shocks in cryptocurrency markets; its practical value consists in the potential use of VYTIndex for risk assessment and for designing arbitrage and hedging strategies during pre- and post-election periods of instability.

Research target: Economics and Management
Language: Russian
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Keywords: sentiment analysisсентимент-анализкриптоактивыкриптовалютный рынок cryptocurrency marketcrypto assetselectoral uncertaintyU.S. presidential electionsuncertainty indexэлекторальная неопределённостьпрезидентские выборы СШАиндекс неопределённости
Publication based on the results of:
Models and methods for identifying patterns in global and national financial markets (2025)
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