Research / Lee
Public on-chain data and documented methods to see who is making money on-chain, and who is setting traps.
A deep dive into Nansen, GMGN, Arkham, Bubblemaps, and DeBank across chain coverage, core features, and pricing models, plus an actionable zero-cost tracking stack.
On-Chain Macro
From network liquidity depth to transaction friction costs, a quantitative framework to cut through manipulated on-chain noise.
From consensus accumulation to concentrated exits: how to measure signal risk rather than just chasing return.
Combining capital, behavioral, and temporal filters to produce a robust smart-money roster with low false positive rates.
Abnormal high-frequency churning and circular wash trading carry distinct signatures that must be pruned to curb false alarms.
A full report every two weeks, with a short data note in between.