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Исследование возможности классификации фондовых рынков различных стран с помощью сетевой модели
Вестник Воронежского государственного университета. Серия: Системный анализ и информационные технологии. 2016. № 3. С. 111–115.
Vizgunov A. N., Наумова А. С.
The globalization process makes all countries stock markets similar to each other. In the paper we try to evaluate this process by analyzing the network models of some countries stock markets by means of neural networks. Our results show that each of the considered countries stock market has a peculiarity that can be used to distinguish the markets.
Ponomarenko A., / Series Computer Science "arxiv.org". 2025.
This paper addresses the challenge of merging hierarchical navigable small world (HNSW) graphs, a critical operation for distributed systems, incremental indexing, and database compaction. We propose three algorithms for this task: Naive Graph Merge (NGM), Intra Graph Traversal Merge (IGTM), and Cross Graph Traversal Merge (CGTM). These algorithms differ in their approach to vertex selection ...
Added: July 30, 2026
Piontkovski D., / Series arXiv "math". 2026.
A noncommutative projective variety is defined, following Artin and Zhang, by a graded coherent algebra 𝐴. The category of coherent sheaves is then the quotient qgr(𝐴) of the category of finitely presented graded modules by the subcategory of torsion modules. We consider the categorical and polynomial entropies of the Serre twist, that is, of the ...
Added: June 23, 2026
Piontkovski D., / Series arXiv "math". 2025.
If a symmetric multilinear algebra is weakly nil, then it is Engel. This result may be regarded as an infinite-dimensional analogue of the well-known Jacobian theorem, which states that if a polynomial mapping has a polynomial inverse, then its Jacobian matrix is invertible. This refines a theorem of Gerstenhaber and partially answers a question posed ...
Added: June 23, 2026
Seul: PMLR, 2026.
Added: June 4, 2026
Chertopolokhov V., Mukhamedov A., Bugriy G. et al., IEEE Access 2026 Vol. 14 P. 14369–14392
This study presents on-the-fly identification and multi-step prediction of nonlinear systems with delayed inputs using a dynamic neural network combined with a smooth projection onto ellipsoids. The projection enforces parameter constraints that guarantee stability, while a Lyapunov–Krasovskii analysis yields computable ultimate error bounds. Riccati-type matrix inequalities are derived, providing an efficient vectorization–projection–devectorization implementation suitable for ...
Added: May 22, 2026
Shipilov F., Barnyakov A., Ivanov A. et al., / Series Physics "arxiv.org". 2026.
A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...
Added: May 19, 2026
Derkacheva A., Sakirkina M., Kraev G. et al., /. 2026.
Comprehensive data on natural hazards and their consequences are crucial for effective for risk assessment, adaptation planning, and emergency response. However, many countries face challenges with fragmented, inconsistent, and inaccessible data, particularly regarding local-scale events. To address this data gap in Russia, we developed an end-to-end processing pipeline that scrapes news from various online sources, ...
Added: April 28, 2026
Ролинский С. О., Dvoynikova A., В кн.: Альманах научных работ молодых ученых Университета ИТМОТ. 2.: Университет ИТМО, 2022. С. 336–340.
В работе рассмотрены основные существующие подходы к автоматическому распознаванию речи, а также проводится сравнительный анализ открытых компьютерных систем распознавания речи. Для экспериментальных исследований эффективности работы рассматриваемых систем используется речевой корпус LibriSpeech. ...
Added: April 24, 2026
Dvoynikova A., Садикова А. А., В кн.: Сборник трудов X Конгресса молодых ученыхТ. 1.: Университет ИТМО, 2021.
В работе рассматривается применение различных планировщиков обучения (англ. scheduler) нейронных сетей для задачи текстонезависимой верификации дикторов. Для экспериментальных исследований использовалась база данных VoxCeleb1, которая содержит в себе различные речевые высказывания 1211 дикторов. В работе проводился анализ влияния различных планировщиков обучения нейронных сетей, представленных в библиотеке PyTorch языка программирования Python, а также 2 алгоритма планировщика, представленных ...
Added: April 24, 2026
Pilé I., Deng Y., Shchur L., / Series arXiv "math". 2026. No. 2604.10254.
We investigate the spatial overlap of successive spin configurations in Markov chain Monte Carlo simulations using the local Metropolis algorithm and the Svendsen-Wang and Wolff cluster algorithms. We examine the dynamics of these algorithms for two models in different universality classes: the Ising model and the Potts model with three components. The overlap of two ...
Added: April 20, 2026
Efremov A., Portnoy S., Волошин А. Д., Первая миля 2025 № 8 С. 20–28
Выполнен комплексный обзор методов машинного обучения (ML), применяемых для повышения устойчивости сигнала к помехам в каналах связи. Бурное развитие поколений беспроводной связи, активная разработка концепции 6G предъявляют высокие требования к задержке, скорости и надежности передачи данных. Традиционные подходы к защите от помех, основанные на строгих аналитических моделях, зачастую не справляются с хаотичной природой плотных гетерогенных ...
Added: April 4, 2026
Gabdullin N., Androsov I., / Series Computer Science "arxiv.org". 2026.
Label prediction in neural networks (NNs) has O(n) complexity proportional to the number of classes. This holds true for classification using fully connected layers and cosine similarity with some set of class prototypes. In this paper we show that if NN latent space (LS) geometry is known and possesses specific properties, label prediction complexity can ...
Added: April 2, 2026
Akaev A., Давыдова О. И., Korotayev A., Философия и общество 2025 № 4(117) С. 5–46
This article presents a comprehensive macroeconomic analysis of countries grouped into civilizational clusters based on a cultural-historical approach. The object of the study is the macroeconomic dynamics of states in the context of civilizational differences, and the subject is the model-based assessment and forecast of GDP growth rates for the period up to 2050. The ...
Added: February 24, 2026
Fayzulin M., Teplova T., Kurkin A., Прикладная эконометрика 2025 Т. 79 С. 99–121
The paper analyses the dynamic connectedness between trading volumes in the Russian stock market and the global cryptocurrency (Bitcoin) market during periods of external shocks (the COVID‑19 crisis and the Russia‑Ukraine conflict) from 2019. Using the TVP‑VAR model and estimates of system variable connectivity, liquidity spillovers (cash flows) are identified between the considered asset classes. For the first time, we analyse the network connectedness of investor sentiment for the most popular Russian stocks and Bitcoin and estimate the role of sentiment in liquidity spillovers. The results demonstrate that Bitcoin’s daily trading volume predominantly acts as a recipient of shocks from the Russian stock market. Meanwhile, the overall coherence in the system was higher during the COVID‑19 crisis period compared to the Special Military Operation (SMO). The study confirms the existence of a correlation between investor sentiment on the Russian stock and cryptocurrency markets. At the beginning of the analyzed period,in 2019, when interest in crypto assets investing began to grow rapidly, this correlation was strongly pronounced.
There is a connectedness between two sentiment indices: on the stock market and crypto‑assets. The intensity of the correlation prevails in the COVID‑19 inception period, significantly exceeding the level observed in the SMO period. This sentiment metrics behaviour may imply adaptation of the Russian stock market to external shocks, as well as retail investors’ expectations of short‑term SMO in early 2022. ...
Added: February 6, 2026
Sizykh N., Кудрявцева Н. С., Управление большими системами: сборник трудов 2025 № 118 С. 250–285
Numerous studies in the field of forecasting securities prices, particularly stock prices, are aimed at finding more accurate and effective models. However, attention to multivariate forecasting, which allows for more accurate forecasts, remains underappreciated, as its implementation requires a significant increase in computing resources. Therefore, the selection of more simplified yet effective models is relevant. ...
Added: February 3, 2026
Morychev G., Sizykh D., Sizykh N., IEEE Access 2025 Vol. 13 P. 213194–213210
One of the main tools for analyzing large volumes of financial data is the use of clustering methods and models, which allow the identification of various patterns. This study examines the problem of clustering time series that reflect the behavior of prices, yields, modes, trends, and a number of related stock indicators. The relevance and ...
Added: February 3, 2026
Морган Р. Б., Grishin V. I., Grishina O. A. et al., М.: ФГБОУ ВО "РЭУ им. Г.В. Плеханова", 2014.
This is a book on modern economics, written mainly in Russian but with a chapter in English. ...
Added: January 27, 2026
Soldatova A., Сберегательное дело за рубежом 2025 № 1 С. 21–33
The article is devoted to the peculiarities of the functioning of the Chinese stock market, its development prospects and opportunities for investors. Key aspects of regulation, classification of shares, stock exchanges and specifics of market participants are considered. Various types of shares, features of each class and access rules for foreign investors are described. The ...
Added: January 21, 2026
Sorokin K., Beketov M., Онучин А. et al., / arxiv.org. Серия cs.SI "Social and Information Networks ". 2025.
Community detection in complex networks is a fundamental problem, open to new approaches in various scientific settings. We introduce a novel community detection method, based on Ricci flow on graphs. Our technique iteratively updates edge weights (their metric lengths) according to their (combinatorial) Foster version of Ricci curvature computed from effective resistance distance between the ...
Added: January 15, 2026
Petrovanov I., Sergeev A., / Series Computer Science "arxiv.org". 2025. No. 2512.18332.
Transport coding reduces message delay in packet-switched networks by introducing controlled redundancy at the transport layer: original packets are encoded into coded packets, and the message is reconstructed after the first successful deliveries, effectively shifting latency from the maximum packet delay to the -th order statistic. We present a concise, reproducible discrete-event implementation of transport coding in OMNeT++, including ...
Added: December 24, 2025
Hessian-based lightweight neural network for brain vessel segmentation on a minimal training dataset
Меньшиков И. А., Бернадотт А. К., Elvimov N. S., / Series arXie "Statistical mechanics". 2025.
Accurate segmentation of blood vessels in brain magnetic resonance angiography (MRA) is essential for successful surgical procedures, such as aneurysm repair or bypass surgery. Currently, annotation is primarily performed through manual segmentation or classical methods, such as the Frangi filter, which often lack sufficient accuracy. Neural networks have emerged as powerful tools for medical image ...
Added: December 1, 2025
Rubchinskiy A., Chubarova D., / Series WP7 "Математические методы анализа решений в экономике, бизнесе и политике". 2025. No. WP7/2025/01.
The article examines one of the most famous examples of socio-economic systems, characterized by significant uncertainty – the S&P-500 stock market, where shares of 500 largest US companies are traded. No assumptions are made about the probabilistic characteristics of the stock market. A flexible algorithm for daily trading has been developed, based on both known fixed data ...
Added: November 9, 2025