Lido on Kusama Selection Procedures
Unlike many of the other Lido staking protocols, validators for Kusama are not chosen through a permissioned set, but through an algorithm that selects operators based off of chain-based performance that maximizes APR.
The gathered and calculated data for each validator and era consists of:
- Era points
- Nominators list
- Stake amount
- Payout rate
This gathered data is aggregated and used to build several metrics for different time periods:
- Operational: last block
- Mid-term: ~1 month
- Short-term: ~1 week
- Long-term: ~6 months
Then the scoring model considers dynamical changes of validators' performance, e.g.:
- Operational data lets us detect oversubscribing, fees increase and slashing.
- Short-term data will show us if some relatively good validator in the long-term goes down or starts to lack in performance.
- Mid- and long-term data will hedge us from choosing validators who show good performance in the short-term but might be unstable in the long run.
APR maximization mechanics are based on validator scores as described above. Using these mechanics, Lido renominates validators as short-term parameters change, so that new scores are kept up to date each week. For more information about the ongoing process and selection algorithm read on:
Lido liquid staking for Kusama upgrades to the uncapped Second Stage
Validators in the Kusama relay chain might be slashed due to different reasons starting from unavailability to double signing. Lido should minimize that risk despite slashing occurring rarely. Our hedging strategy is based on stake diversification, which means we distribute pooled stake to several nominators or staking ledgers.
The automated selection process has led to Lido on Kusama driving more effective rewards for stKSM stakers. Per research conducted by MixBytes, the average Kusama staking return is ~ 17% vs. Lido on Kusama boasting a ~ 25% return (data as of 12/5/22).
Possible factors of validator underperformance:
Prospective validators interested in improving their performance to be selected by the algorithm would be well served to address the following causes of lower returns:
- Bad Server Configuration
- Suboptimal configuration, including inadequate hardware specs, lack of storage, memory, or network performance are among potential factors. There are recommendations given on hardware requirements in the Polkadot Wiki.
- Small Amount of Stake
- As per the Polkadot Wiki, the minimum requirement for inclusion in the active set it is equal to 4,504 KSM. Validators with smaller amount of stake could lead to low activity ratios and lower APRs for nominators.
- Node Oversubscription
- Validator nodes can be oversubscribed, which leads to bad APR for nominators. Per the allocation model 5,000 KSM is the optimal stake, and every node having more than this amount will begin to underperform.
- Improper Maintenance and Upkeep
- Misconfigured infrastructure or improper deployments, in addition to slashing, are among factors that may lead to lower APRs.