Risk-Aware Range and Position Sizing for CLMM Agents

Concentrated-liquidity pools (e.g. Merchant Moe's incentivized mETH/USDe ranges) reward tight bands but punish them with impermanent loss and out-of-range idle capital when volatility spikes, making range width and position size a hard online decision for an agent. Current bots use fixed heuristics rather than volatility-aware sizing tied to a drawdown budget. A days-scale prototype can be measured on fee capture, time-in-range, max drawdown, and Sharpe-like risk-adjusted return against a passive wide-range LP.