Pegged Algorithm: Cruise Control

Pegged & stable pairs have become extremely popular with the addition of new products into crypto such as LRTs, yield-bearing stables, and new L1s or L2s with their own unique staked derivative tokens & stables. Typically, these pools are also among the largest and most heavily used on any given exchange as well, perfect setting for the optimal strategy. For pegged pairs, liquidity is concentrated into a smaller range; usually only a handful of ticks around the price. Since pegged strategies should in theory stay in lockstep, we simply let the market do what it does, with the utmost unshattered love and faith.

However, pegged pairs are characterized by wicks, above and below the current price, due to outsized players entering & exiting meaningful positions relative to the amount of available liquidity. At the moment one of these meaningful exits or entries causes a breach of the price range, our strategy does not jump the gun to rebalance. Instead, we focus on the “fair” value of the pegged tokens against each other, and effectively rebalance only when our range is breached, paired with a significant change in this fair value. This fair value is, effectively, a drift, that we measure through historical data and noise filtering, and reset at every rebalance.

To further improve this method, we utilize a median filter to read the price so that even though a small lag is introduced in rebalances, a huge amount of price noise is eliminated. Stable pairs can be optimized with the same strategy as pegged pairs, with the main difference that the fair value doesn’t change over time due to the stable nature of both tokens.