Method and data

• For defining the 10 largest liquidity pools (in terms of value locked), I used: ethereum.erc20_balances

• For swap sizes, I used ethereum.dex_swaps

• For pool_name, I used ethereum.dex_liquidity_pools

Introduction

Sushiswap is one of the most popular decentralized cryptocurrency exchange (DEX) and automated market maker (AMM) which is built on Ethereum. On Sushiswap users are able to swap (trade) tokens through Liquidity Pools. In fact, liquidity pools are instrumental to trading in decentralized exchanges. This dashboard will focus on the 10 largest liquidity pools (in terms of value locked) and investigate how the daily average swap through those LPs changes over time.

Results

10 largest liquidity pools on SushiSwap

To identify the largest liquidity pool, we can take different approaches. One approach can be to take a snapshot and rank liquidity pools in terms of their locked value at that certain date. Another way can be to consider a period of time and rank liquidity pools based on the average locked value in that period of time.

I believe the latter approach makes more sense. I considered a three month period average locked value ($). The table below lists the largest liquidity pools in terms of average daily locked value in 90 days ending on January 15th 2022.

Daily swap size

Daily swap size can be measured as the number of swaps as well as the total volume of swaps per day.

Below graph shows both the daily number and volume of swaps over time.

As can be seen from the graph, in overall, volume of swaps has less variation comparing with number of swaps. The data shows that since November 2021 the level of number of swaps has decreased. the volume also shows a slight downward trend.

The graph below show a correlation between the daily number of swaps and volume of swaps. Breaking down the data into pools, we can see that some pools has in general higher both number and volume of swap (for instance USDC-WETH LP) and some has high volume with relatively lower number of swapping (for instance wbtc_weth LP).

From the graphs below we can see that some unusual picks are resulted from a performance of one PL rather all pools together. For instance, on October 15th an spark in OHM-DAI LP swapping resulted in an increase in daily size of swaps.

Data also shows that the size of the locked value does not necessarily associate with the size of swaps. For instance, ILV-WITH LP is the largest pool but has a considerable share of total swap size neither in terms of volume nor in terms of number.

Summary of findings

The data shows:

• There is a correlation between the number and volume of swaps.

• There is no clear relationship between the size of pools and the size of swaps (this should be statistically tested with a larger sample of pools).

• The size of swaps for some of the pools are almost constant over time, while for others is seasonal.

• There is a slight downward trend in both the number of and volume of swaps since three months ago. This trend can be explained by looking at the general trend of the crypto market since November 2021, when bitcoin started its decline.