To make sure the liquidation process can be made smoothly on Furion, which plays a very important role in efficient borrowing & lending, minimizing the risk of bad debts, and serving leveraged trading, we simulate and stress-test liquidation scenarios by modeling all kinds of market movements, to see if the liquidators are sufficiently incentivized.
We also compare the AMM-style fragmented lending(Furion) with peer-to-peer lending mechanisms(like BendDAO) and find that, to the extent that liquidity depth allows, the former has a higher incentive effect on liquidators while improving liquidation efficiency, thus making it more conducive to build an organic market.
  1. 1.
    The price of simulated NFT follows Geometric Brown Motion, with drift and volatility as hyperparameters.
  2. 2.
    There are 4 transactions per day on average following the Poisson Process.
  3. 3.
    The depth for the AMM pool(k^2) is fixed at 500,000. No liquidity goes in and out during the simulation.
  4. 4.
    The price for the AMM pool aligns perfectly with the NFT market.
Simulation Result
Liquidation on Furion is carried out in a more timely manner, saving time and reducing volatility costs.