Hypothesis: On-Chain Volume Anomaly Detection Can Predict Short-Term Token Price Surges With >60% Precision Using Composite Behavioral Signals

Background

Decentralized exchange (DEX) trading generates rich real-time behavioral data: transaction counts, buy/sell ratios, liquidity dynamics, and wallet activity patterns. Unlike centralized exchange data, on-chain signals are tamper-evident and accessible without privileged access.

Hypothesis

A composite anomaly detection system monitoring ETH-based DEX tokens using the following signals — (1) volume-to-liquidity ratio spikes, (2) unique buyer acceleration relative to exponential moving average, (3) buy/sell ratio dominance with minimum transaction threshold, and (4) liquidity growth momentum — can predict short-term price surges (>15% within 4 hours) with precision exceeding 60%, significantly outperforming random baseline (~10-15% for low-cap tokens on any given period).

Proposed Mechanism

Each signal captures a distinct behavioral dimension: Vol/Liq ratio captures capital flow intensity relative to pool depth; buyer EMA acceleration distinguishes organic accumulation from wash trading; buy/sell ratio (min 15 txns) reduces noise from thin orderbooks; liquidity growth detects smart money adding conviction. The composite score creates a Bayesian-style filter — multiple independent signals firing simultaneously reduces false positive rate multiplicatively.

Testable Prediction

Running this scanner on Ethereum mainnet with score threshold >=5 should yield precision >60% (alerts lead to >15% price movement within 4h) and false positive rate <40%.

Current Status

Live validation in progress on Ethereum mainnet as of April 2026. Calibrating thresholds against real-time outcomes.