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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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Эскалация человеческой субъективности в экзистенциально-философской критике техники

С. 354–357.
Pavlov I.
Language: Russian
Text on another site
Keywords: philosophy of technologyфилософия техникиVladimir BibikhinВладимир Бибихин

In book

Современные тенденции кросс-культурных коммуникаций: Сборник материалов II Международной научно-практической конференции, 11 ноября 2020 г.
Краснодар: Издательство КубГТУ, 2020.
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