标题： 基于阈值的方法检测加密货币拉高出货策略：处理市场噪声 显示英文标题

标题： Detecting Crypto Pump-and-Dump Schemes: A Thresholding-Based Approach to Handling Market Noise

摘要： 我们提出了一种简单而稳健的无监督模型，用于检测在Poloniex交易所平台上列出的代币的拉高出货事件。 通过结合基于阈值的标准与指数加权移动平均线（EWMA）和波动性测量，我们的方法能够有效区分真实的异常情况与轻微的交易波动，即使对于流动性较低和长期不活跃的代币也是如此。 这些特性带来了独特的挑战，因为标准的异常检测方法通常会过度标记微不足道的交易量激增。 我们的框架通过根据观察到的特定交易模式调整价格和交易量阈值来克服这一问题，从而得到一个在高真正阳性检测率和最小噪声之间取得平衡的模型。 显示英文摘要

摘要： We propose a simple yet robust unsupervised model to detect pump-and-dump events on tokens listed on the Poloniex Exchange platform. By combining threshold-based criteria with exponentially weighted moving averages (EWMA) and volatility measures, our approach effectively distinguishes genuine anomalies from minor trading fluctuations, even for tokens with low liquidity and prolonged inactivity. These characteristics present a unique challenge, as standard anomaly-detection methods often over-flag negligible volume spikes. Our framework overcomes this issue by tailoring both price and volume thresholds to the specific trading patterns observed, resulting in a model that balances high true-positive detection with minimal noise.