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用流动性跳跃与扩散检测加密货币刷量交易

文章 arXiv papers · 作者: Qi Deng et al.
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总结

本文提出通过衡量短期流动性波动来检测加密货币市场中可能存在的刷量交易。文章将流动性跳跃定义为波动幅度，将流动性扩散定义为其波动率。建议的信号是这两个指标同时升高，并以US股票作为基准进行评估，旨在区分与操纵相关的活动和一般流动性变化。

论文报告称，模拟监管干预移除可能的刷量交易后，流动性扩散显著下降，而流动性跳跃基本保持不变。文章通过一个模型解释这一模式：操纵性交易者会同时提高价格压力的水平和变动性，而被动投资者只影响其水平。该方法被提出作为投资者和监管机构的监测工具，但摘录未提供样本细节、阈值，或所述比较和模拟之外的验证。因此，这些指标代表一种拟议的市场质量信号，并不能确证任何特定交易活动就是操纵行为。

核心观点

  • 流动性跳跃衡量短期流动性波动的幅度，流动性扩散衡量其波动率。
  • 所提刷量交易信号是两个流动性指标同时上升。
  • 以US股票为基准评估加密货币流动性模式。
  • 模拟移除可能的刷量交易后，流动性扩散下降，而流动性跳跃基本保持不变。
  • 该框架可辅助监测，但不能证明每个被标记的波动都是操纵行为。

标签

加密资产市场微观结构统计学风险管理
全文
# Liquidity Jump, Liquidity Diffusion, and Crypto Wash Trading


# Liquidity Jump, Liquidity Diffusion, and Crypto Wash Trading









We develop a new framework to detect wash trading in crypto assets through real-time liquidity fluctuation. We propose that short-term price jumps in crypto assets results from wash trading-induced liquidity fluctuation, and construct two complementary liquidity measures, liquidity jump (size of fluctuation) and liquidity diffusion (volatility of fluctuation), to capture the behavioral signature of wash trading. Using US stocks as a benchmark, we demonstrate that joint elevation in both liquidity metrics indicates wash trading in crypto assets. A simulated regulatory treatment that removes likely wash trades confirms this dynamic: it reduces liquidity diffusion significantly while leaving liquidity jump largely unaffected. These findings align with a theoretical model in which manipulative traders amplify both the level and variance of price pressure, whereas passive investors affect only the level. Our model offers practical tools for investors to assess market quality and for regulators to monitor manipulation risk on crypto exchanges without oversight.

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。