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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.
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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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Dual Identity in Repressive Contexts: An Agent-Based Model of Protest Dynamics

Social Science Computer Review. 2023. Vol. 41. No. 6. P. 2249–2273.
Alexander Petrov, Andrei Akhremenko, Sergey Zheglov

Protest campaign movements are often carried out by coalitions rather than by homogeneous groups. Accordingly, an opposition member has both a narrow partisan identity and a broad allopposition identity. Seeking to prevent mass political participation, autocracies can repress protesters regardless of their group membership or apply the “divide and conquer” principle, targeting specific groups. Any strategy of repression drives some dynamics of identity. For instance, broad repression may rally the opposition by increasing broad identity at the expense of narrow identity. This dynamic of identity causes complex dynamics of motivation for participation in the protest, which affects the turnout. The paper introduces a computational model to describe the dynamics of the turnout. The model employs the social identity model of collective action (SIMCA) and accounts for the dual protest identity.

Research target: Political Science, International Relations, and Public Administration Computer Science
Language: English
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Keywords: decision-makingпринятие решенийpolitical mobilizationполитический протестполитическая мобилизацияагентное моделированиеcomputational social scienceвычислительные социальные наукиpolitical protestagent-based model
Publication based on the results of:
Psychological, social and communicative factors of political behavior (2023)
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