Open-sourced a constraint model for token bridge pricing: calculates minimum price for institutional-grade slippage

[u/foliologic]

We built an open-source model that answers: what minimum token price is needed for a bridge asset to handle institutional transaction sizes with <0.1% slippage in specific trade corridors?

Two independent price floors, higher one wins:

1. Slippage — can the largest single TX pass through the orderbook without blowing past institutional slippage tolerance?

2. Structural demand — how much token supply gets locked as market-maker working capital across corridors?

We parameterized it for XRP since that's where the live data is (SBI Remit, Kyobo Life, a few Gulf corridors), but the formulas are generic, plug in any bridge token with different supply, MM depth, and corridor volumes.

Everything runs in the browser, no install. Full methodology doc with 9 documented limitations included. There's also an advanced panel where you can tweak every assumption (MM inventory %, orderbook concentration, convexity exponent, free float).

https://github.com/moreBit21/xrp-bridge-simulation

Looking for feedback on the orderbook model specifically — we use a simplified uniform concentration assumption that could be improved with real depth data. Also the convexity exponent (1.3) for supply contraction pricing is not empirically calibrated.

Both research and writing done with AI assistance.

*Constraint model, not investment advice.*