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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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University students' economic literacy depends not only on their field of study but also on their interest in economics, the learning environment, and family financial practices. For example, students who received pocket money irregularly tend to perform better on economic literacy tests than their peers who received financial support on a regular basis. These findings come from a study conducted by HSE University involving more than 1,100 students from five Russian universities. The findings have been published in Cakrawala Pendidikan.
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Integration of Distributed Ledger Technology and Modern Smart Grids: An Outlook

P. 182–191.
Komarov M. M., Markova M., Ometov A.

Today, the evolution of electrical grid systems is pacing towards interconnected Smart Grids mainly driven
by governmental activities worldwide. This step brings additional challenges from the data storage perspective since
conventional centralized systems may not handle the growing data volumes arriving from various sources. Thus, new
distributed solutions must be introduced to allow flexible and on-the-fly enablers to such tremendous data flows. One
of the potential candidates is integrating Blockchain-powered Distributed Ledger Technology (DLT) to achieve an immutable record of manipulating electricity from production to end-user delivery. In this paper, we study the relation of said diverse technological components inter-operation, related challenges, and solutions proposed by research and federal regulators. Based on the literature review, we draft the recommendation for the wide-scale architecture of the future combined solution.

Language: English
Full text
DOI
Keywords: электроэнергетикаdistributed information systemsраспределенные информационные системытехнология распределенного реестраDistributed Ledger TechnologySmart Gridselectricity supply industrysmart grids

In book

IEEE 23rd Conference on Business Informatics (CBI)
IEEE Computer Society, 2021.
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