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myco-bonding-curve/docs/08-dynamic-weights.md

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08: Dynamic Weights

Source

  • Protocol: Balancer
  • Files: GradualValueChange.sol, LBPool.sol (V3), quantamm_math.py
  • Repos: balancer/balancer-v2-monorepo, balancer/balancer-v3-monorepo, balancer/balancer-maths

Rationale for MYCO

Static bonding curves have fixed geometry — the price surface never adapts. Dynamic weights allow the MYCO bonding surface to evolve over time:

  1. Token launch: LBP-style weight schedule for initial distribution (start 95/5 MYCO/USDC, gradually shift to 50/50)
  2. Adaptive pricing: Oracle-driven multipliers let the surface respond to market conditions
  3. Governance updates: Smooth transitions between parameter sets (no discontinuities)
  4. Reserve rebalancing: As target allocations change, weights interpolate smoothly

Two mechanisms:

  • GradualValueChange: Linear interpolation on a schedule (deterministic)
  • QuantAMM multiplier: Oracle sets a velocity, weight drifts linearly until next update (reactive)

Formulas

GradualValueChange:

progress = (t - t_start) / (t_end - t_start)
value(t) = start_value + progress * (end_value - start_value)

Clamped: before start → start_value, after end → end_value.

QuantAMM multiplier:

weight(t) = base_weight + multiplier * (t - last_update_time)

Oracle updates (base_weight, multiplier) at each block/epoch.

Parameters

Parameter Effect
start/end values What the weight changes between
start/end times Duration of the transition
multiplier Rate of change per time unit (oracle-driven)
min/max weight Bounds to prevent extreme allocations

Implementation

See src/primitives/dynamic_weights.py