I’ve done some research into crypto markets recently and derived a methodology that I believe could address several issues the DODO team has identified around dynamic updating of the liquidity concentration parameter. The details can be found in a paper I uploaded on github but it in essence boils down to tracking order flow in a LP pool and using a measure of statistical distance to quantify how much curvature (i.e. the liquidity parameter k in DODO’s PMM curve) the pool should have at any given time.
From my understanding DODO could be the first AMM to leverage something like this approach and this could help reduce the market risk that liquidity providers are exposed to as well as attract more trading to the exchange during calm periods.