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  • Влияет ли финансовое состояние компаний на прогностическую точность DCF-модели?
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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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?

Влияет ли финансовое состояние компаний на прогностическую точность DCF-модели?

Финансовый журнал. 2025. Т. 17. № 6. С. 99–112.
Федоров Н. С.

The DCF model is one of the most commonly used models in valuing companies for investment deci sions. Nevertheless, estimating the accuracy of this model remains an important research question. This article presents an assessment of the accuracy of DCF model specifications based on analyzing the variance of fair share prices of companies listed on the S&P 500 stock index. The fair prices from the DCF model are calculated using artificial intelligence algorithms. The analysis of the DCF model’s accuracy includes a comparison of fair prices with market and realized prices, which increases the reliability of the empirical analysis. The study shows that the accuracy of fair prices calculated on the basis of the DCF model specifications varies depending on the financial performance of companies.

Research target: Economics and Management
Language: Russian
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DOI
Text on another site
Keywords: искусственный интеллектfair priceсправедливая ценаDCFоценка стоимости компанийcompany valuation artificial intelligenceDCF
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