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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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Межпартийное противостояние в период разработки законопроекта о Парламенте 1911 года

Российский научный журнал. 2011. № 24. С. 39–50.
Kovalev I. G.

This article explores the confrontation between the Conservative and Liberal parties in the UK according the House of Lords reform during the preparation of the draft Act of Parliament of 1911. A link of this issue with other relevant aspects of social, financial and constitutional-legal policy is identified. The causes of the inter-party dialogue beginning, the secret talks in the Constitutional Conference, the circumstances surrounding the inability of party leaders to reach an agreement are analyzed.

Priority areas: sociology law humanitarian
Language: Russian
Keywords: Conservative Partyреформа Палаты лордовКонсервативная партияHouse of Lords ReformLiberal PartyParliament bill 1911suspensory vetoЛиберальная партияЗаконопроект о Парламенте 1911 г.отлагательное ветоconstitutional conferenceRoyal guaranteesпожалование пэрских титуловконституционная конференциякоролевские гарантии
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