How does it work ?

Monitoring and Selection Process : The AI model continuously monitors a predefi ned array of pools, focusing on identifying those with the top APYs. This process is not about gambling on a single pool; instead, it's about systematically scanning for the best yield opportunities at any given moment.
Top Performing Pools Analysis : After identifying the top performers, typically the top three pools with similar APYs, the AI model proceeds to a deeper analysis. This involves estimating the costs, fees,checking the minimum lock-up period (if any) and calculating the potential outcomes associated with investing in each of these pools.
Decision-Making Criteria : If the initial analysis doesn't yield a clear winner (by at least 20% yield difference), the AI models - Naive Bayes Classifi er and k-Nearest Neighbours - are deployed to assess which pool has the lowest risk of asset price drop. This assessment is crucial as even a high APY can be offset by a signifi cant drop in the reward asset value, leading to impermanent loss.
Risk Mitigation Strategy : By employing this method, our AI Aggregator aims to choose the most optimal pool, balancing high yield potential with minimal risk. The focus is not solely on the highest immediate return but on sustaining yield optimization over time, minimizing risks such as asset price volatility.

Last updated 1 year ago

Monitoring and Selection Process : The AI model continuously monitors a predefi ned array of pools, focusing on identifying those with the top APYs. This process is not about gambling on a single pool; instead, it's about systematically scanning for the best yield opportunities at any given moment.
Top Performing Pools Analysis : After identifying the top performers, typically the top three pools with similar APYs, the AI model proceeds to a deeper analysis. This involves estimating the costs, fees,checking the minimum lock-up period (if any) and calculating the potential outcomes associated with investing in each of these pools.
Decision-Making Criteria : If the initial analysis doesn't yield a clear winner (by at least 20% yield difference), the AI models - Naive Bayes Classifi er and k-Nearest Neighbours - are deployed to assess which pool has the lowest risk of asset price drop. This assessment is crucial as even a high APY can be offset by a signifi cant drop in the reward asset value, leading to impermanent loss.
Risk Mitigation Strategy : By employing this method, our AI Aggregator aims to choose the most optimal pool, balancing high yield potential with minimal risk. The focus is not solely on the highest immediate return but on sustaining yield optimization over time, minimizing risks such as asset price volatility.

Last updated 1 year ago