8 signals in Composite Alpha.
Detects genuine vs spoofed liquidity in crypto order books by analyzing bid/ask placement patterns, cancellation rates, and fill ratios across exchanges.
Identifies institutional-grade order flow through size clustering, timing patterns, and execution algorithm detection in perpetual futures markets.
Measures when trending moves are losing internal support from volume, momentum, and order flow convergence in crypto perpetual futures.
Quantifies the probability that current market orders are informed (toxic) vs uninformed flow, using microstructure analysis of perpetual futures.
Detects when overcrowded leveraged positioning is beginning to unwind, measuring exit pressure and cascade probability across perpetual futures.
Combines price momentum with order flow and open interest data to determine whether momentum has genuine conviction or is fading.
Identifies forced selling capitulation being absorbed by limit order walls, signaling potential reversal points in perpetual futures.
Detects divergence between market narrative (sentiment, social data) and actual on-chain and order flow data in crypto markets.