lp-math
LP Math — AMM Liquidity Provision Mathematics
Automated Market Makers (AMMs) replace traditional orderbooks with liquidity pools. Instead of matching buyers and sellers, a mathematical formula determines prices based on reserve ratios. Liquidity providers (LPs) deposit both assets into a pool and earn fees from every trade.
Understanding the math behind AMMs is essential for:
- Evaluating whether providing liquidity is profitable after impermanent loss
- Estimating price impact before executing large trades
- Comparing capital efficiency across pool types (constant product vs concentrated)
- Calculating expected fee revenue for a given pool position
Related skills: See impermanent-loss for IL calculations, yield-analysis for LP yield modeling, liquidity-analysis for pool depth assessment.
1. Constant Product AMM (xy = k)
The foundational AMM model used by Raydium V4 and most Solana DEXes.
Core Invariant
More from agiprolabs/claude-trading-skills
pandas-ta
Technical analysis with 130+ indicators using pandas-ta for crypto market data
108risk-management
Portfolio-level risk controls, drawdown management, exposure limits, and circuit breakers for crypto trading
77feature-engineering
Feature construction from market data for ML trading models including price, volume, on-chain, and microstructure features
77trading-visualization
Professional trading charts including candlesticks, equity curves, drawdowns, correlation heatmaps, and return distributions
77signal-classification
ML trading signal classifiers using XGBoost and LightGBM with walk-forward validation, SHAP feature importance, and threshold optimization
74market-microstructure
DEX orderflow analysis, trade classification, buyer/seller pressure, and microstructure signals for Solana tokens
74