# πInnovation in Market Maker Services

β Efficient asset screening and allocation algorithm: HMM is a relatively classic learning model. L2FINANCE uses HMM to make a rational machine learning mechanism for the market maker model, which can accurately calibrate the accuracy, reduce transaction friction costs, optimize the entire market-making operation logic, and accelerate processing and concurrency.

β‘The steps to simplify the operation by smart contracts: AMMs are one of the most impactful DeFi innovations. Through the AMM automated market maker model, L2FINANCE can create and operate publicly available on-chain liquidity for a range of different derivatives, improving transaction efficiency and accuracy.

β’Eliminate impermanent losses: Due to price fluctuations or excessive trading volume of trading assets, market makers cannot adjust the weight ratio of assets in time, which may lead to losses for market makers. L2FINANCE's liquidity market maker service adopts a global liquidity model, which makes transaction fees low and has no slippage. At the same time, AIGC technology is used to realize AI automatic optimization strategy to further reduce impermanent losses caused by market fluctuations. β£Global risk factor model benchmarks:

Adopt AIGC technology combined with a global risk factor model. The formula is: R = rf + b1πΉ1 + b2πΉ2 β¦ + bnπΉπ + π. R is the expected return of the factor model, that is, the benchmark rate of return, rf is the risk-free interest rate, bn is the exposure of the portfolio to the factor, πΉπ is the factor risk premium, that is, the excess return of the factor relative to the risk-free return, and π is the residual item. It mainly depends on whether it is possible to obtain excess returns relative to the benchmark rate of return.

Last updated