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STTM: an efficient approach to estimating news impact on stock movement direction
PeerJ Computer Science. 2022. Vol. 8. Article e1156.
Open text data, such as financial news, are thought to be able to affect or to describe stock market behavior, however, there are no widely accepted algorithms for extracting the relationship between stock quotes time series and fast-growing textual representation of economic information. The field remains challenging and understudied. In particular, topic modeling as a powerful tool for interpretable dimensionality reduction has been hardly ever used for such tasks. We present a topic modeling framework for assessing the relationship between financial news stream and stock prices in order to maximize trader’s gain. To do so, we use a dataset of economic news sections of three Russian national media sources (Kommersant, Vedomosti, and RIA Novosti) containing 197,678 economic articles. They are used to predict 39 time series of the most liquid Russian stocks collected over eight years, from 2013 to 2021. Our approach shows the ability to detect significant return-predictive signals and outperforms 26 existing models in terms of Sharpe ratio and annual return of simple long strategy. In particular, it shows a significant Granger causal relationship for more than 70% of portfolio stocks. Furthermore, the approach produces highly interpretable results, requires no domain[1]specific dictionaries, and, unlike most existing industrial solutions, can be calibrated for individual time series. This makes it directly usable for trading strategies and analytical tasks. Finally, since topic modeling shows its efficiency for most European languages, our approach is expected to be transferrable to European stock markets as well.
Publication based on the results of:
Guerreiro I., Sergey Skorokhod, di Volo M. et al., Communications in Nonlinear Science and Numerical Simulation 2027 Vol. 164 Article 110954
The collective dynamics of spiking networks of neurons has been of central interest to both computational
neuroscience and network science. Over the past years, a new generation of neural
population models based on exact reductions (ER) of spiking networks have been developed.
However, most of these efforts have been limited to networks of neurons with simple dynamics
(e.g. the ...
Added: October 29, 2026
Association for Computational Linguistics, 2026.
While Large Language Models (LLMs) have revolutionized NLP, they remain prone to hallucinations, reasoning “mode-collapse” in open-ended generation, and a lack of factual provenance. The Automated Knowledge Base Construction (AKBC) workshop addresses a key missing piece of the generative era: structured knowledge. Knowledge Bases (KBs) serve as ground truth for fact verification, the semantic backbone ...
Added: October 28, 2026
Nikitiuk B., Lenev D., Pisarev V. et al., Journal of Colloid and Interface Science 2026 Vol. 718 Article 140444
Hypothesis:Accurate determination of interfacial tension values is crucial for many modeling applications in the oil and gas industry. However, many of the presently used empirical and theoretical models show poor prediction accuracy and do not allow for direct consideration of the concentrations of gases and salts dissolved in the system as well as the specific ...
Added: October 28, 2026
Deshchenya V., Nikolay D. Kondratyuk, Sivakova A. et al., Chemical Engineering Sciences 2027 Vol. 337 Article 124616
Accurate prediction of complex formulation viscosity is crucial for the lubricant industry and engineering processes. However, developing generalizable models remains challenging due to the complexity of industrial mixtures and the scarcity of public experimental data, often resulting from corporate proprietary restrictions. This study presents a machine-learning workflow for viscosity estimation from a proprietary pseudonymized dataset, ...
Added: October 28, 2026
Zubov A., Zubov A., Малявко, Я. et al., Computer Physics Communications 2025 Vol. 317 Article 109860
The concept of representative volume (REV, or RVE in material sciences) is the cornerstone of continuum scale models – one needs to get the volume big enough so that it could be represented with an averaged value (scalar, vector or tensorial, etc.). While REV should be established in all larger scale simulations, this is rarely ...
Added: October 28, 2026
Roman Prosvirnin, Suslov A., Aleksei Soldatov et al., Computation 2026 Vol. 14 No. 10 Article 261
Abstract
Safety-aligned language models often encode that a request is harmful yet still comply with it. We turn this gap between internal recognition and observable behavior into an inference-time defense. The proposed activation-steering method uses a multiplicative operator that amplifies the residual-stream component along a harm-recognition direction. Intervention strength scales with the model’s own assessment of ...
Added: October 27, 2026
Aleksei Samarin, Nazarenko A., Nazarenko D. et al., Big Data and Cognitive Computing 2026 Vol. 10 No. 11 P. 1–52
Camera traps are a key tool for non-invasive wildlife monitoring, yet models trained on existing benchmarks often generalize poorly to new regions due to domain shift, class imbalance, and natural variability in illumination, season, and background. We introduce PACTraD, a benchmark of 116,973 annotated camera trap images collected in a protected area of the Baikal ...
Added: October 27, 2026
IEEE, 2026.
Proceedings of the X Scientific School "Dynamics of Complex Networks and their Applications"
(DCNA'2026) contain papers of reports of scientists and specialists in the field of intelligent technologies,
engineering education, research and design of complex networks.
DCNA'2026 was held from 10 to 12 September 2026 in Moscow, Russia, as a part of the International
Forum on Artificial Intelligence and ...
Added: October 26, 2026
Maddalena L., Yildiz B., Del Vecchio Blanco F. et al., Scientific data 2026 P. 1–20
We addressed the task of chemical characterization of the aerosol emitted by heated tobacco products (HTPs) and of the smoke emitted by conventional/commercial cigarettes, usually adopted as a reference. Emphasis was placed on quantifying constituents for enabling the identification of novel compounds through targeted and untargeted analyses, and the evaluation of reductions in toxicant exposure under ...
Added: October 26, 2026
Obsie E. Y., Zhan Y., Liu Y., Engineering Research Express 2026 Article 7
Maintaining plant health is crucial for crop quality, food security, and agricultural productivity. Although deep learning methods have shown strong potential for species, disease, and severity classification, most existing approaches tackle these tasks separately, failing to exploit shared representations and interdependencies among them. Furthermore, the variability of disease symptoms, such as subtle differences in size, ...
Added: October 22, 2026
Lev Pyatko, Sergey Aksenov, Regular and Chaotic Dynamics 2026 Vol. 31 No. 5 P. 794–813
In the circular restricted three-body problem, families of periodic and quasi-periodic orbits exist in the vicinity of the libration points and are of significant interest for practical applications. This work presents a neural network-based algorithm for orbit construction and station-keeping, applicable to both periodic and quasi-periodic orbits near collinear libration points. The method employs a ...
Added: October 19, 2026
Vorontsova T., М.: Академия, 2025.
The textbook has been prepared in accordance with the requirements of the federal state educational standards for secondary vocational education and is intended for studying the professional modules “Information Security in Information and Telecommunication Systems and Networks Using Software and Hardware‑Software Tools, Including Cryptographic Protection Tools” and “Information Security in Automated Systems Using Software and ...
Added: October 19, 2026
Aleksei Samarin, Nazarenko A., Nazarenko D. et al., Machine Learning and Knowledge Extraction 2026 Vol. 8 No. 10 Article 330
Automated microscopic image analysis is essential for quantitative microbiology, yet manual acquisition and generic recognition models struggle with morphological variability and scene artifacts. We address both ends of this pipeline. First, we present a low-cost, open-source acquisition system, based on an Arduino UNO R3 microcontroller and NEMA 17 stepper motors, that automates focusing, magnification, and ...
Added: October 14, 2026
Springer, 2026.
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the XIV International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2025). The carefully selected papers cover ...
Added: October 13, 2026
Springer, 2026.
This book offers a comprehensive overview of the latest research, innovations, and practical applications in the field of sustainability, with a focus on construction materials and their use in building and civil engineering structures. As an outcome of the 3rd International Conference on Sustainability: Developments and Innovations (ICSDI 2026), this book presents a selection of ...
Added: October 13, 2026
Dmitriev A., Kornilov V., Batienkov R., Lecture Notes in Civil Engineering 2026 Vol. 886 P. 249–255
Numerous studies have provided compelling evidence that the probability distribution of avalanche sizes follows a power law, and that 1/f noise is present in the stochastic dynamics of landslides. We present a theoretical explanation of these phenomena within the framework of self-organized criticality theory, proposing a discrete-time model in the form of a sandpile cellular ...
Added: October 13, 2026
Dmitriev A., Shulman I., Lebedev A., Studies in Computational Intelligence 2026 Vol. 1265 P. 266–273
A discrete-time model is presented for the self-organization of the X/Twitter social network to the edge of a phase transition, characterized by avalanche-like propagation of information in the network. The model is based on the analogy between the critical dynamics of the X social network and sandpile cellular automata with Manna rule on the Chung-Lu ...
Added: October 13, 2026
Makarov D. M., Kalikin N., Fashchevsky K. A. et al., Electrochimica Acta 2026 Vol. 579 Article 150159
Machine learning (ML) has become a powerful tool for accelerating the development of carbon-based supercapacitors;
however, most published models assume that a single predictive framework can describe both conventional
porous carbons and hybrid carbon electrodes. Here, we test this assumption using a comprehensive
benchmark dataset and an extended literature-curated dataset enriched with synthesis- and electrolyte-related
descriptors. Three ML algorithms ...
Added: October 13, 2026
Zhang Z., Ilvovsky D., Information Processing and Management 2026 Vol. 63 No. 7
Transformer-based Large Language Models (LLMs) rely on Key-Value (KV) cache to accelerate autoregressive decoding, but memory and compute requirements still grow with context length, limiting deployment on resource-constrained devices. Existing training-free KV cache compression methods mainly rely on attention-driven retention heuristics, which may under preserve structurally informative tokens under tight cache budgets, especially when such ...
Added: October 13, 2026
No Species Is an Island, Entire of Itself: Genetic Speciation Algorithm with Interplay among Species
Gromov V., Sohrabi M., Fathollahi-Fard A., International Journal of Engineering, Transactions B: Applications 2027 Vol. 40 No. 5 P. 1437–1460
This paper, with a particular emphasis on Genetic Algorithm (GA), proposes a novel approach that integrates clustering mechanisms, predator-prey dynamics, and a distinctive selection strategy for generating subsequent populations. The proposed evolutionary algorithm, referred to as Genetic Speciation Algorithm with Interplay Among Species (GSAIS), is comprehensively evaluated against several variants of GAs as well as ...
Added: October 12, 2026
Alexandrov D., Vasilevsky V., Rezunik L. et al., Труды Института системного программирования РАН 2026 Т. 38 № 5 С. 73–90
Large language models demonstrate limitations in tasks that require precise information retrieval from very long input sequences. This limitation affects code generation in large object-oriented systems, where correctness depends on complex inter-class dependencies and the analysis of long execution traces that exceed standard context window sizes. This paper presents JavaCapsule, a technology for automated generation ...
Added: October 12, 2026
Брычков М. Е., Незнанов А.А., Программирование 2026 № 4 С. 50–66
The matrix profile (MP) quickly became one of the most important time series preprocessing methods when it was introduced in 2016, facilitating the solution of a wide range of time series analysis problems, in particular anomaly and pattern detection problems. The high significance has led to the emergence of various tools for MP calculating, but ...
Added: October 9, 2026
Lysenok N., Маркова Ю. Е., Финансовый журнал 2026 Т. 18 № 4 С. 45–63
The article discusses the application of clustering methods to form an optimal investment portfolio
that allows the investor to achieve an effective risk-reward ratio. Three popular clustering methods,
K-Means, MeanShift, and DBSCAN, are examined. The article focuses on the DBSCAN clustering method
and highlights its advantages over other clustering methods in the context of financial data analysis.
DBSCAN is ...
Added: August 27, 2026
Соколова Е. Н., Grigoreva M., Знак: проблемное поле медиаобразования 2026 № 1(59) С. 92–101
The article analyzes representations of grandmothers’ and grandfathers’ images in the digital family discourse of the Russian social media segment. Based on a corpus of more than two million public posts from September 2023 to September 2024 collected via Brand Analytics, we extracted a subcorpus of 82 138 posts mentioning the older generation. The study ...
Added: June 30, 2026