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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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Influence of Cultural Factors on Organizational Performance of Multinational Corporations: A Bibliometric Review from 1983 to 2020

Qeios. 2024.
Wang F., Barajas A.

Cultural factors are critical in shaping the organizational performance of multinational corporations (MNCs) operating across diverse countries and cultures. This study conducts a comprehensive bibliometric analysis to explore scientific developments in this research area from 1983 to 2020, based on 856 documents published across 195 journals indexed in the Web of Science. The analysis provides insights into (i) productivity and performance trends within the field, (ii) the most influential countries, regions, journals, authors, and citations, and (iii) frequently occurring keywords that highlight future research directions. This study captures the historical evolution of research on cultural factors, providing a valuable baseline for understanding the pre-COVID-19 context and enabling MNCs to better navigate cross-cultural communication and collaboration in an increasingly complex global environment.

Research target: Economics and Management Social Sciences
Language: English
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Keywords: международный бизнескультурные факторыsystematic literature reviewcultural factorsсистематический обзор литературы International businessBibliographic StudyMultinational Corporations (MNCs)Web of Science (WoS)Библиографическое исследованиеТранснациональные корпорации (ТНК)Web of Science (WoS)Pre-COVID-19Пре-COVID-19
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