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News
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.
June 4, 2026
Machine Learning Models Can Help Reduce Volatility and Boost Stock Market Returns
The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.

 

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Climate change exposure and corporate strategic aggressiveness: Evidence from Chinese listed companies

Economic Analysis and Policy. 2025. Vol. 88. P. 26–53.
Zhao F., Wang J., Chen Q.

This paper examines the strategic implications of corporate climate change exposure in the context of Chinese listed firms. Drawing on MD&A textual disclosures from 2007 to 2021, we construct a firm-level index of climate exposure and find that greater engagement with climate issues leads to more aggressive strategic behavior. This relationship is robust to a range of identification strategies and alternative specifications. Mechanism analysis reveals that climate exposure reduces financing constraints and stimulates risk-taking, prompting firms to act more decisively. The effect is more pronounced among non-state-owned enterprises, ESG-leading firms, those embedded in Confucian cultural regions, firms led by optimistic managers and more climate sensitive firms. We further find that opportunity-related climate signals—rather than physical risks or regulatory pressure—are the primary drivers of strategic change, and that these changes translate into tangible actions, such as increased green innovation and investment intensity. These findings highlight the economic relevance of climate-related information and underscore its role in shaping long-term corporate behavior and resource allocation in emerging markets.

Research target: Economics and Management
Language: English
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Keywords: изменение климатастратегические измененияфинансовые ограниченияfinancing constraintsRisk-takingClimate changeStrategic changeChinese listed companiesПринятие рисковКитайские публичные компании
Publication based on the results of:
Institutions, human capital and regional Development: historical analysis and contemporary challenges (2025)
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