Relevance
5/10
Directly relevant to DeFi/DEX quantitative trading and AMM market-making strategies. The finding that LP supply does not respond significantly to take-rate cuts constrains fee-controller simulations and informs liquidity provision strategies on Uniswap v3. However, relevance to traditional quantitative trading (equities, futures, FX) is limited. The methodology (event-study DiD on on-chain data) is transferable to other protocol governance evaluations relevant to crypto-native trading strategies.
Implementation Complexity
8/10
High complexity: requires reconstructing pool state from ordered on-chain events (Swap/Mint/Burn/Collect), tick-book initialization, time-weighted active liquidity computation across multiple bands, LP lifecycle tracking by owner-range key, JIT share identification, and fee income scaling by per-token decimals. Uses a custom Rust toolchain for memory-bounded reconstruction of ~70M events, cross-validated against independent reconstruction. Inference pipeline involves multiple R packages (fixest, fwildclusterboot, HonestDiD, sensemakr, ebal, fect, fdapace). Reproducing the full design requires on-chain data access, Rust compilation, and careful adherence to frozen specification.
Reproducibility
5/5
Exceptionally high reproducibility: frozen, hash-checked panel with SHA256 manifest per file; deterministic reconstruction from raw on-chain logs via a self-contained Rust toolchain; independent reconstruction cross-checked row-for-row; estimator parity between Rust and R; full code and data pipeline available on GitHub; pre-specified design with no post-hoc specification selection; all gates, seeds, and transforms logged.