Introduction

• Sushi is a community-driven organization built to solve what might be called the “liquidity problem.” One could define this problem as the inability of disparate forms of liquidity to connect with markets in a decentralized way, and vice versa. While other solutions provide incrementally progressive advances toward solving the problem of liquidity, Sushi’s progress is intended to create a broader range of network effects. Rather than limiting itself to a single solution, Sushi intertwines many decentralized markets and instruments.
• The core products include: a decentralized exchange, a decentralized lending market, yield instruments, an auction platform, an AMM framework and staking derivatives.
• Providing liquidity to pools in order to enable decentralized exchange and yield instruments is very important to any decentralized platform including Sushiswap.

In this dashboard, we will explore Sushiswap’s liquidity provider stats on Ethereum.

Method

• SushiSwapRouter Contract '0xd9e1ce17f2641f24ae83637ab66a2cca9c378b9f':
  • Add liquidity functions: ['0xe8e33700','0xf305d719'].
  • Remove liquidity functions: ['0x02751cec','0x2195995c','0x5b0d5984','0xaf2979eb','0xbaa2abde','0xded9382a'].
• MasterChefV1 Contract '0xc2edad668740f1aa35e4d8f227fb8e17dca888cd':
  • Deposit function: '0xe2bbb158'.
  • Withdraw function: '0x441a3e70'.
• MasterChefV2 Contract '0xef0881ec094552b2e128cf945ef17a6752b4ec5d':
  • Deposit function: '0x8dbdbe6d'.
  • Withdraw function: ['0x0ad58d2f','0xd1abb907','0x2f940c70'].
  • Harvest function: ['0x18fccc76','0x4f70b15a'].

Glossary

What’s the total no. of unique LP?

86.9K unique addresses have added liquidity to LP pool.

What’s the ratio between YFs vs. LPs?

43% of LPs are also Yield Farmers, or the ratio between Yield Farmers vs. LPs is 0.43.

What’s the average no. of LP positions opened by each unique wallet address?

On average, number of LP position opened by each wallet is 1.69 (i.e. on average, a liquidity provider add liquidity in 1.69 pools).

What’s the ratio of liquidity (Based on TVL) owned by Protocols vs. Retail in both LP Pool and Yield Farms?

To answer this question, I will breakdown total liquidity provided by 2 groups:

• Protocols: labeled addresses in table ethereum.core.dim_labels.
• Retails: the rest.

1. Of all $ amount of assets have been added to both LP Pool and Yield Farm, Retail account for 98.2%, Protocols only account for 1.8%. Or the ratio of liquidity between Protocols and Retail is 0.018.
2. Of all $ amount of assets have been added to LP Pool, Retail account for 98.1%, Protocols only account for 1.9%. Or the ratio of liquidity between Protocols and Retail is 0.019.
3. Of all $ amount of assets have been deposited to Yield Farm, Retail account for 99.3%, Protocols only account for 0.7%. Or the ratio of liquidity between Protocols and Retail is 0.007.

→ As the number in (3) lower than in (1) and (2), it appears that Retail LPs are more likely to stake their SLP tokens in Yield Farm after add liquidity to LP Pool than Protocol LPs.

What is the percentage (%) increase/decrease of LP Providers in Sushi over the last 1 year?

To answer this question, I will compare several metrics of Aug 21, 2022 and Aug 21, 2021.

• If we look at the daily trend, on Aug 21, 2022, there were 94 LPs, 15% of 605 LPs on Aug 21, 2021, or 85% decrease.
• If we look at the rolling 7 days trend, on Aug 21, 2022, there were 514 LPs, 13% of 3911 LPs on Aug 21, 2021, or 87% decrease.
• If we look at the rolling 30 days trend, on Aug 21, 2022, there were 2,276 LPs, 16% of 14,123 LPs on Aug 21, 2021, or 84% decrease.

→ Last 1 year, Sushi’s LPs has dropped significantly.

Next, let’s evaluate the profitability of an LP Provider & Yield Farmer.

1. Correlation between profitability vs. length of time

1.1. Correlation between profitability vs. length of time of an LP

First, let’s evaluate the distribution of various target segments who provide liquidity (LP).

What is the percentage of total positions completely removed when LPs remove liquidity?

• Answering this question to understand more about LPs behavior when they remove liquidity and help answering the next question.
• This is calculated by comparing removed SLP tokens vs. added SLP tokens of each LP in each pool.
• Exclude positions with removed SLP tokens > added SLP tokens, which might due to data omission.

→ 86.3% of total positions are completely removed when LPs remove liquidity from LP Pool.

Is there a correlation between profitability vs. length of time of an LP?

To answer this question, let’s look at average % ROI of each length of time between add and remove liquidity (LP duration).

• We can see on the chart below, % ROI and LP duration are quite correlated if the LP duration is between 27 days and 151 days.
• Correlation between % ROI and LP duration is not conclusive outside the 27-151 days range.

What is the percentage of total positions completely removed when Yield Farmers withdraw SLP tokens?

• Answering this question to understand more about YFs behavior when they withdraw SLP tokens and help answering the next question.

• This is calculated by comparing withdrawn SLP tokens vs. deposited SLP tokens of each YF in each farm.

• Exclude positions with removed SLP tokens > added SLP tokens, which might due to data omission.

→ 93.7% of total positions are completely withdrawn when YFs withdraw SLP tokens from Farms.

1.2. Correlation between profitability vs. length of time of a YF

How does a YF claim pending rewards through MasterchefV1?

• Answering this question to understand more about how MasterchefV1 operate.

• From this document and the chart below, I understand that a YF claim pending rewards when deposit more SLP tokens to a Farm or withdraw SLP tokens from the Farm. This is how the MasterchefV1 contract is designed.

→ 83.5% of total rewards are claimed when YFs deposit more SLP tokens to Farms.

How does a YF claim pending rewards through MasterchefV2?

• Answering this question to understand more about how MasterchefV2 operate.

• From this document and the chart below, MasterchefV2 is an improvement to MasterchefV1 I understand that a YF claim pending rewards when harvest rewards, withdraw SLP tokens, or deposit more SLP tokens to a Farm from the Farm.

→ 88.4% of total rewards are claimed when YFs harvest from Farms.

How many farms does a YF normally have?

Let’s look at % share in total farmers by number of farm bucket.

67.2% of total farmers only deposited in 1 farm.

Top 3 buckets are 1, 2, and 3 farms with 90,68% of total farmers.

→ Yield Farmers normally have 1 - 3 farms.

Is there a correlation between profitability vs. length of time of a YF?

To answer this question, let’s look at average Rewards of each length of time between deposit and withdraw SLP tokens (YF duration).

> Before looking at actual data, let’s review the basic mechanism of Yield Farming. Assuming that rewards schemes are the same, and amount of deposited SLP tokens are the same, the longer staking time, the more yield a YF get. So in theory, Yield Farm profitability and length of staking time are correlated.

Now, let’s look at the chart to see what actual data tells us.

Note: I exclude outliers to better observe trend.

The up trend of average $ rewards is clearly observed up to the 240 days. This indicates that normally, the longest staking time of a YF is 240 days.

→ Though in theory, a YF yield more rewards with longer staking time. Sushi’s YFs appear to not seeing significant benefit of yield farming longer than 240 days or ~ 8 months.

2. Correlation between profit vs. time of withdrawal

2.1. Correlation between profit vs. time of withdrawal of a LP from LP Pool

Correlation between profit vs. hour of day of withdrawal from LP Pool

Note: I use median $ profit of all withdrawals to minimize outliers’ effect.

→ It appears that withdrawals happened in very early hours (0-3) of the first half and very early hours (13-15) of the second half of a day have bigger losses than other hours. And these hours don’t dominate in % of total withdrawals, thus we can eliminate the effect of dominant volume in correlation above.

Correlation between profit vs. day of week of withdrawal from LP Pool

Note: I use median $ profit of all withdrawals to minimize outliers’ effect.

→ It appears that withdrawals happened in the first 2 days of a week have bigger losses than other days. And these days don’t dominate in % of total withdrawals, thus we can eliminate the effect of dominant volume in correlation above.

2.1. Correlation between profit vs. time of withdrawal of a YF from Farm

Correlation between profit vs. hour of day of withdrawal from Farm

Note:

• I use median $ profit of all withdrawals to minimize outliers’ effect.
• I exclude rewards claimed through deposit function to focus on intentional withdrawal through withdraw and harvest functions.

→ It appears that withdrawals happened in very early hours (0-3) and working hours (6-15) of a day have bigger profit than other hours. And these hours don’t dominate in % of total withdrawals, thus we can eliminate the effect of dominant volume in correlation above.

Correlation between profit vs. day of week of withdrawal from Farm

Note:

• I use median $ profit of all withdrawals to minimize outliers’ effect.
• I exclude rewards claimed through deposit function to focus on intentional withdrawal through withdraw and harvest functions.

→ It appears that withdrawals happened in the middle of a week (Wed - Fri) have bigger profit than other days. And these days don’t dominate in % of total withdrawals, thus we can eliminate the effect of dominant volume in correlation above.

3. Correlation between profitability vs type of pool

Note:

Stable pools are pools which have one of 3 tokens USDC, USDT, DAI as token0 and token1.

WETH pools are pools which have WETH as token0 or token1.

WBTC pools are pools which have WBTC as token0 or token1.

Other pools are the rest.

Both WETH pools and WBTC pools has average % ROI > 10%, while Stable pools average % ROI is only 0.07%, and Other pools average % ROI is -1.38%.

→ Higher profitability in WETH pools and WBTC pools than the rest.

Conclusion

• There are 86.9K unique addresses have added liquidity on average to 1.68 pools, of which 43% have also deposited their SLP tokens to yield farm, normally they deposit in 1-3 farms.
• 98% of total LPs are Retail LPs, only 2% are Protocol LPs. Retail LPs are more likely to yield farm than Protocol LPs.
• Last 1 year, Sushi’s LPs has dropped significantly (84% to 87% depends on time frame).
• About correlation between profitability vs. length of time:
  • In the period from 27 days to 151 days between add and remove liquidity, it appears that profitability and length of time in LP Pool are correlated.
  • Though in theory, a YF yield more rewards with longer staking time. Sushi’s YFs appear to not seeing significant benefit of yield farming longer than 240 days or ~ 8 months.
• About correlation between profit vs. time of withdrawal of a LP from LP Pool:
  • It appears that withdrawals happened in very early hours (0-3) of the first half and very early hours (13-15) of the second half of a day have bigger losses than other hours.
  • It appears that withdrawals happened in the first 2 days of a week have bigger losses than other days.
• About correlation between profit vs. time of withdrawal of a YF from Farm:
  • It appears that withdrawals happened in very early hours (0-3) and working hours (6-15) of a day have bigger profit than other hours.
  • It appears that withdrawals happened in the middle of a week (Wed - Fri) have bigger profit than other days.
• About correlation between profitability vs type of pool:
  • On average, WETH pools and WBTC pools have higher profitability than Stable pools and Other pools.

Thanks for reading!

Reference