Try Quests to earn cryptoUNI V3 Pool Bound Distances
Uni V3 introduced an upper and lower bound system which can be set by liquidity providers to maximize their profit. In this dashboard, we will explore the average distance between the boundaries and which factors are affecting them.
Are the average distance affected by a position's size? Based on the graph below, yes it does. Based on observation, the average distance is lower the larger the position. One could say that due to a larger position's size, impermanent loss will be much more unbearable than the ones with a smaller size. To remedy this, the average distance must be more precise to get a worthwhile return.
The top 10 Uni V3 liquidity pools by volume in July are found out and their positions analyzed. Based on the findings, the average distance of a pool is most affected by the volatility of the token pairs, followed by its fee and lastly its volume and liquidity. The average distance is further affected by the size of the position, where the higher the position, the lower the average distance.
So what are the other factors? The graph below shows the volume of each of the pools, by comparing it to the graph of average distance, there isn't much correlation. The same goes to the total liquidity of the pool. Upon further inspection, the average distance seems to be related to the fee of the pool, where the higher the fee, the higher the average distance. This can be determined from the fact that, on average, 0.05% fee pools have lower average distances while 0.3% fee pools have higher distances.
By combining (by addition) the volatility of the tokens for each token pair, it is found out that the average distance is highly affected by the tokens' volatility, where the distance is larger when the volatility is high. This is expected because if one sets too narrow a gap for volatile tokens, the price will go out of bounds quite easily and thus resulting in a lot less profit for providing liquidity. In spite of this, we still see a difference in average distance when two different liquidity pools with the same paired tokens, so there must be other factors that's affecting the average distance.
Since the average distance are price movement percentages, the most obvious place to look for the cause of differing average distances for token pairs is the volatility of the tokens in each pair. The volatility in this case is the difference in max price divided by the min price of the tokens in July. July is chosen for the calculation of volatility because the pools in question are the top 10 pools in July. Based on the graph below, we see that token pairs that contain highly volatile tokens have the largest distances.
The average distance in ticks between the upper and lower boundary is calculated. Since ticks are essentially blocks that are 0.01% price movement away from adjacent blocks, we can translate the block distance into % distance, which is shown in the graph below. Based on the graph, we can see that MKR-WETH and UNI-WETH pairs have the highest average distance while stablecoin pairs have the least distance.
The graph below shows the top 10 Uni V3 pools by liquidity, these are shown just as a reference.
The top liquidity pools were decided by ranking all the Uni v3 liquidity pools based on their average liquidity in July to find out the latest trends, since Uni V3 is only 3 months old at the time of writing.