Automated Concentrated Liquidity Management (ACLM)

Amplified Finance's ACLM (ALM v3) is an AI-driven framework engineered to optimize liquidity provisioning in DeFi through dynamic, data-anchored strategies. It maximizes capital efficiency and fee capture while actively reducing impermanent loss, particularly for correlated pairs and asset derivatives.

Dynamic Range Optimization ACLM continuously recalibrates liquidity positioning using real-time market signals.

• Real-Time Price Analysis: Monitors TWAP deviations and price momentum to anticipate range breaches

• Volatility-Adaptive Ranges: Widens or narrows positions based on realized volatility and options-implied levels

• Automated Rebalancing Triggers: Adjusts ranges when price deviates beyond sigma thresholds or trend shifts

• Market Depth Integration: Sizes ranges relative to pool liquidity distribution to avoid dry zones

This ensures capital remains concentrated in zones of highest trading activity.

Intelligent Fee Tier Management ACLM dynamically selects and switches fee tiers across pools to maximize net yield.

• Volume & Turnover Analysis: Identifies high-fee-capture pools using real-time trading intensity metrics

• Historical Performance Modeling: Evaluates fee accruals per epoch to rank tier efficiency

• Gas-Adjusted Profitability Engine: Only executes tier switches when expected fees exceed transaction costs

• Strategic Tier Placement: Targets underutilized but high-volume tiers where fee share exceeds opportunity cost

Result: persistent alignment with the most profitable market-making layers.

Cross-Pool Yield Optimization Capital is not managed per pool, but as a unified, multi-venue strategy.

• Coordinated Deployment: Distributes liquidity across DEXs to capture volume spillover effects

• Real-Time Profitability Comparison: Ranks pools by fee yield, depth stability, and MEV exposure

• Strategic Capital Allocation: Rebalances across venues based on relative edge, not just absolute returns

• Yield Synergy Exploitation: Identifies pairs where liquidity in one pool enhances returns in another, such as wstETH/ETH and cbETH/ETH

This creates a compounding advantage through systemic positioning.

Risk & Efficiency Controls Institutional-grade safeguards ensure capital preservation.

• Correlation-Based Position Sizing: Reduces exposure when pair correlation drops below threshold, for example <0.92 for synthetic derivatives

• Impermanent Loss Mitigation: Uses delta-neutral heuristics and rebalancing buffers to limit drawdowns

• Unified Risk Monitoring: Tracks portfolio-level exposure to volatility spikes, oracle failures, and protocol risks

• Gas-Efficient Automation: Bundles adjustments and uses predictive gas pricing to minimize operational cost

All actions are constrained by on-chain VaR models and governance-set limits.

AI Agent Swarm Integration ACLM is powered by a decentralized swarm of AI agents:

• Strategy Agent: Generates range and tier proposals based on multi-source data

• Validation Agent: Simulates outcomes and verifies risk compliance

• Execution Agent: Implements changes via low-slippage, atomic transactions

Each agent operates within strict, auditable boundaries, ensuring robust, transparent automation.

Conclusion Automated Concentrated Liquidity Management (ACLM) transforms passive liquidity provision into an active, intelligent strategy. By combining AI-driven range optimization, cross-pool yield synthesis, and institutional risk controls, it delivers superior capital efficiency and risk-adjusted returns, setting a new standard for automated market-making in DeFi.