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WebCryptoAgent：结合网络证据与快速加密风险控制

文章 arXiv papers · 作者: Ali Kurban et al.
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总结

WebCryptoAgent是一种短周期加密货币交易框架，结合网络内容、社交情绪和OHLCV市场数据。该框架分配专门处理不同模态的智能体来分析各类信息来源，再将其评估结果汇总为证据文档，以支持置信度校准后的决策。其设计旨在减少由噪声或虚假相关性驱动的决策。

该框架还将按小时运行的策略推理与秒级风险模型分开。这样，风险组件无需等待较慢的交易循环即可检测突发冲击并采取干预。作者报告了在真实加密货币市场进行的实验，并称该方法提升了交易稳定性、减少了不必要的交易活动，也比基准系统更能应对尾部风险。所提供的描述未说明数据集、评估指标、数值结果或这些改善成立的条件，因此仅凭摘要无法评估证据的强度和普适性。

核心观点

  • 不同智能体分别分析网络、情绪和OHLCV输入，再汇总各自的证据。
  • 置信度校准后的推理旨在减少基于虚假信号的决策。
  • 按小时进行的策略决策与更快速、独立的风险模型配合运行。
  • 作者报告称，真实市场实验中交易稳定性更高，尾部风险处理也有所改善。

标签

加密资产市场情绪市场微观结构风险管理机器学习
全文
# WebCryptoAgent: Agentic Crypto Trading with Web Informatics


# WebCryptoAgent: Agentic Crypto Trading with Web Informatics









Cryptocurrency trading increasingly depends on timely integration of heterogeneous web information and market microstructure signals to support short-horizon decision making under extreme volatility. However, existing trading systems struggle to jointly reason over noisy multi-source web evidence while maintaining robustness to rapid price shocks at sub-second timescales. The first challenge lies in synthesizing unstructured web content, social sentiment, and structured OHLCV signals into coherent and interpretable trading decisions without amplifying spurious correlations, while the second challenge concerns risk control, as slow deliberative reasoning pipelines are ill-suited for handling abrupt market shocks that require immediate defensive responses. To address these challenges, we propose WebCryptoAgent, an agentic trading framework that decomposes web-informed decision making into modality-specific agents and consolidates their outputs into a unified evidence document for confidence-calibrated reasoning. We further introduce a decoupled control architecture that separates strategic hourly reasoning from a real-time second-level risk model, enabling fast shock detection and protective intervention independent of the trading loop. Extensive experiments on real-world cryptocurrency markets demonstrate that WebCryptoAgent improves trading stability, reduces spurious activity, and enhances tail-risk handling compared to existing baselines. Code will be available at https://github.com/AIGeeksGroup/WebCryptoAgent.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。