Multi-Model Decision Layer

The Multi-Model Decision Layer is the core intelligence unit of the system. Through parallel multi-model computation and dynamic weight switching, it enables intelligent strategy generation.

Market Structure Models: analyze liquidity depth, spread distribution, and changes in market impact costs to assess execution feasibility and potential trading costs.

Volatility Risk Models: based on historical volatility, abnormal spikes, leverage concentration, and other indicators, identify market risk conditions and quantify potential losses.

Trend/Range Models: utilize methods such as moving averages, Bollinger Bands, ADX, and range oscillators to determine trend direction and support/resistance zones, providing execution references for strategies.

Capital Behavior Models: analyze whale movements, cross-chain migration, address-cluster capital flows, and changes in capital concentration to capture Alpha opportunities.

Dynamic Weighting Mechanism: evaluates market regimes in real time (trend vs. range, stable volatility vs. spikes, sufficient liquidity vs. insufficient liquidity), and weights model outputs accordingly to optimize strategy adaptability.

Technical Infrastructure: supports parallel training and inference with TensorFlow / PyTorch models, combined with reinforcement learning and multi-agent collaborative strategy optimization.

Description: The Multi-Model Decision Layer transforms market states into executable strategies, forming a systematic AI-driven decision-making capability.