Risk Adjusted

This strategy allows you to automatically rebalance the best risk/yield allocation

The risk-adjusted allocation strategy provides a way to earn the best rate at the lowest risk-level. The risk-management algorithm takes account of the total assets within a pool, incorporates underlying protocol rate functions and levels of supply and demand, skimming protocols with a bad score/rate mix, and finally determining an allocation that achieves the highest risk-return score possible after the rebalance happens.

It has been developed in collaboration with DeFiScore, a framework for quantifying risk in permissionless lending pools. DeFiScore is a single, consistently comparable value for measuring protocol risk, based on factors including smart contract risk, collateralization, and liquidity. The model outputs a 0–10 score that represent the level of risk on a specific lending protocol (where 10 is the upper bound = lowest risk, and 0 is the lower bound = highest risk).

You can read more about the risk assessment model here.

Technical details

With this strategy we are trying to find the right balance between risk and returns. We are weighting score and apr based on k parameter. This can be modeled as follows:

max q(x)=i=0nxitot(nextRatei(xi)maxNextRate+knextScorei(xi)maxNextScorek+1)max\ q(x) = \sum_{i=0}^{n} \frac{x_i}{tot} * (\frac{\frac{nextRate_i(x_i)}{maxNextRate} + k * \frac{nextScore_i(x_i)}{maxNextScore}}{k + 1})

where n is the number of lending protocols used, x_i is the amount (in underlying) allocated in protocol i , nextRate(x_i) is a function which returns the new APR for protocol i after supplying x_i ,nextScore(x_i) is a function which returns the new Score for protocol i after supplying x_iamount of underlying, maxNextRate is the highest rate of all implemented protocols after supplying x_i amount, same for maxNextScore with regard to the score, tot is total amount to rebalance, finally k is a coefficient for expressing weights of score and apr (k = 1 means equally weighted, currently k = 2 so score weights twice the APR).

tot=i=0nxitot=\sum_{i=0}^{n} x_i