The liquidity incentives formula Liquidity Mining - Mango Markets
Liquidity “points” are defiend as:
points= reverse_dist * reverse_dist * time_on_book * quantity
and the incentives are paramaterised at the moment with max_depth_bps=200
This means that large orders which are 100bp+ out are hogging a lot of the MNGO reward distributions, where they have minimal risk of being hit.
For three users providing same liquidity size for same time, one at 1bp away from price, one at 50bp away from price, and 100bp away and 150bp away from price their points are:
points_1bp = 199^2 = 39,601
points_50bp=150^2 = 22.500
points_150bp = 50^2= 2,500
This means that someone who is risk-averse and wants to just farm MNGO while totally avoiding to get hit can simply quote 1.76 BTC at 0.5% wider and get the same exact points, or 3.96 BTC at 1% wider to get the same points, or 15.8 BTC at 1.5% wider
Furthermore, it would be easier for them to do this at higher leverage (up to 10x) which, while would be riskier, is actually not as risky because they can requote much more frequently to avoid getting hit.
And, this is what is observed, just days after this liquidity mining has gone live:
Lots of large orders 50bp+, and 100bp+, who are earning more than those with less capital quoting nearer the front of the book.
This has to stop and we need to incentivise the people closer to the book more
There are a number of ways to fix this, in Discord a couple of things have been suggested:
(a) reduce max_depth_bps to 100
(b) change the points formula from quadratic function of reverse_dist to a higher power
The problem with (a) is that it attaches zero value to liquidity outside of 1% of price. This is not realistic because liquidators and arbitrageurs need deeper liquidity to feel secure about taking positions and being able to offload the risk on the Mango books.
The main thing we need to do is enhance the reward given closer to the price so that it’s not as easy for people to add size further away to gain points.
Here’s the current curvature using quadratic:
Here’s comparison with doing reverse_dist^3, reverse_dist^4 , and reverse_dist^8 instead (normalised to quadratic approach):
As you see, we can effectively drop the max bps without totally eliminating some benefit to those who are further out. This gives the benefit of more people getting MNGO rewards, even if a little, to boost distribution in general
If anyone has other ideas on this we can discuss in this thread