Herding unmasked: Insights into cryptocurrencies, stocks and US ETFs

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(2), P. e0316332 - e0316332

Published: Feb. 3, 2025

Herding behavior has become a familiar phenomenon to investors, with potential dangers of both undervaluing and overvaluing assets, while also threatening market stability. This study contributes the literature on herding by using recent dataset, covering most impactful events years. To our knowledge, this is first examining across three different types investment vehicle observing at community (subset) level. Specifically, we explore in each separate type vehicle, namely stocks, US ETFs cryptocurrencies, Cross-Sectional Absolute Deviation model. We find mostly similar patterns for stocks ETFs. Subsequently, same experiment implemented combination all vehicles. For deeper investigation, adopt graph-based techniques including Minimum Spanning Tree Louvain detection partition into smaller subsets detect subset. that exists times subset level, although perhaps not superset tends stem from specific solely impact assets. Lastly, financial contagion effects between these vehicle. Results show only have tendency propagate trading behaviors especially cryptocurrencies but self-reinforcing behavior, acting as drivers their own trends.

Language: Английский

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Predicting spatio-temporal traffic flow: a comprehensive end-to-end approach from surveillance cameras

Transportmetrica B Transport Dynamics, Journal Year: 2024, Volume and Issue: 12(1)

Published: July 22, 2024

Traffic flow forecasting is an essential aspect of intelligent traffic management. It enables timely and proactive management modern transport systems, increasing efficiency resilience. However, accurately predicting short-term challenging due to its uncertain interconnected nature. Traditional methods like loop detectors high-resolution cameras have limited scalability. To address this, we propose a two-stage approach using low-resolution surveillance cameras. The first stage involves vision-based data extraction module with calibration, vehicle detection, tracking. Integration Region Interest, fine-tuning, post-processing improves the robustness videos. In second stage, novel deep learning model extracts spatio-temporal features from historical for prediction. proposed outperforms STGCN model, achieving 11.19% increase in MAE, 12.37% improvement RMSE 4.97% reduction inference time. These advances highlight potential further research applications field.

Language: Английский

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Domestication and Foreignisation in Translation Studies: A Bibliometric Analysis of WoS Core Journal Articles

Journal of Intercultural Communication, Journal Year: 2024, Volume and Issue: unknown, P. 13 - 22

Published: Oct. 21, 2024

Translation plays a vital role in globalisation by acting as bridge of cross-cultural communication. The current study investigated 232 published Web Science (WoS) core journal articles on domestication and foreignisation concepts translation studies the past two decades through bibliometric analysis. Specifically, evolution with major research trends, burst detection, keyword timelines, citation networks is delineated. A geographical map portraying global spread field collaborative also provided. results demonstrate progressive changes terms focus methodology, underscoring adaptive trend strategies across cultural contexts. In-depth insights are provided way scholarly dialogue foreignization, well their pivotal roles practices.

Language: Английский

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Attribute enhanced random walk for community detection in attributed networks

Neurocomputing, Journal Year: 2024, Volume and Issue: 615, P. 128826 - 128826

Published: Nov. 8, 2024

Language: Английский

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