Strategies
Auto Regression Strategy
Flype's first strategy, applies auto regression statistics models to uniswap pools' data in order to find the narrowest price range that will capture a higher share of the fees for a given position.
Let's take a closer look at how it works:
In case the simulation shows that the new price range adjustment is profitable, the strategy manager will execute the ‘executiveRebalance’ function with the new price range and the liquidity Uniswap V3 pool will be altered.
Fetch all data metrics of a Uniswap V3 pool, including: all swaps data, pools’ price history and virtual liquidity history before and after each swap.
The fetched data is analyzed through an autoregressive model in order to generate an estimation of the narrowest price range which is expected to capture 95% of the pool’s transaction fees.
Simulating the new price range in order to determine if it will capture more fees than its execution costs, such as swap fees, gas and price slippage. The leftovers that will stand idle as a result of the rebalance are also taken into account.
Auto Compounding
Flype's automated bots constantly monitors the fees accrued on the Uniswap liquidity position. Once the required gas costs in order to execute the auto compounding are below 1% of the accumulated fees, the bot executes the rebalance function on the vault's smart contract which withdraws these funds and redeposit them into the Uniswap liquidity position.
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