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Subject
News
September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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Устойчивость причинно-следственной связи между ценой на нефть и российским фондовым индексом

Вопросы статистики. 2025. Т. 32. № 4. С. 37–48.
Свиридов О. И.

The article is devoted to analyzing the stability of the causal relationship between changes in oil prices and the dynamics of the Russian
stock market, whose primary indicator is the RTS Index. The main goal of the research is to test the hypothesis of the persistence of a stable
influence of oil price shocks (driven by fluctuations in supply, demand, and supply expectations) on the RTS Index amid structural shifts in
the Russian economy during the period from 1999 to 2019.

The novelty of the approach proposed by the author lies in applying the core tool for studying causality – the Structural Vector Autoregres-
sion (SVAR) model – to decompose oil price shocks into their constituent sources based on the reasons for their occurrence and to assess the

RTS Index's response to them. Additionally, the Moving Block Bootstrap (MBB) method is used to test the significance of changes in the stock
index's impulse responses. The research results indicate that, despite the detection of a structural break in the stock market variable equation,
the differences in its impulse responses to oil price shocks before and after this break are statistically insignificant, which confirms the proposed
hypothesis. Thus, it can be argued that a stable causal relationship exists between oil prices and the Russian stock index throughout the entire
analyzed period, including global economic crises and domestic economic transformations in Russia.
The study contributes to understanding the long-term dynamics of the interconnections between the commodity and financial sectors of
the Russian economy, highlighting the critical importance of the energy component for the stability of the national stock market.

Research target: Economics and Management
Language: Russian
Full text
DOI
Text on another site
Keywords: фондовый рынокиндекс РТСSVAR-модельMoving Block Bootstrap функции импульсных откликов нефтяные цены, индекс РТС
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