Top Kashi Pairs

    Find the top 5 Kashi pairs on Ethereum based on TVL. Choose one that you like and describe the following information: 1. How many people are borrowing this pair at the moment? 2. How much collateral has each user added to the pair? 3. How many users have already partially paid their loans?

    Top 5 Pools

    Let's first look at the top 5 Kashi pools based on Total Volume (wasn't able to get TVL). I cannot find the Kashi pairs on Dex Screener either, so I'll go by Total Volume ever through the pool.

    NOTE: I've cleaned up the km in front so it's easier to read.

    Loading...

    In terms of total volume in AMOUNT_USD (which is not always filled on the ethereum_code.ez_token_transfers table), we get that xSUSHI/DAI, WBTC/DAI, WETH/DAI, AAVE/DAI and LINK/DAI have had the most volume going through them since inception.

    Loading...

    Number of borrowers for the pairs

    Let's now look at the number of borrowers for the given pairs

    xSUSHI/DAI-LINK seems to be the most borrowed one and it follows that it also has the highest all-time volume through it.

    Again, we see here the discrepancy of the TVL vs Total Volume, maybe these are not in fact the 5 highest TVL pairs.

    Let's look at the ones on Dex Screener and sort them by liquidity.

    db_img

    I was not able to find more than 2 of these that have a Kashi alternative, so let's just look at what people are borrowing in general. With respect to # of Transactions for LogAddCollateral and then sorted by Total volume we get the following.

    Loading...

    xSUSHI/DAI and LINK/DAI are still here but we can see that the rest are not seen in the previous one. It's still interesting though to see what the most borrowed pairs are in terms of also volume that goes through them.

    Average Collateral Adder per User per Pool

    Let's now look at the average value ($) adder per user per pool.

    First on the established top 5 pools in terms of Total Volume and then the top 5 pools in terms of borrow or LogAddCollateral.

    Loading...

    It seems that LINK/DAI has a much higher collateral value per user than all others. with WBTC/DAI being the second one with the highest collateral added.

    Loading...

    In this one also we can see that the LINK pools have the most added collateral value out of all the different pools per user. Is it that LINK has underperformed and that the users who borrowed using LINK find themselves needing to add more and more collateral to maintain their borrow position?

    db_img

    Or maybe something else? For that, there are more whales borrowing on that Kashi pair compared to every other pair and this is why we see this kind of pattern?

    Partially or not. First in terms of all-time volume than in overall collateral removed terms.

    Loading...
    Loading...

    A lot of whales potentially on the AAVE/DAI one from looking at both of the above, then similarly for WBTC/DAI and LINK/DAI. Not so clear for WETH/DAI and for xSUSHI/DAI I am guessing smaller wallets withdrawing their collateral, which brings the average down when looking at both transaction count and average collateral removed.

    Let's now look at the top 5 pools in terms of where collateral has been removed from.

    Loading...
    Loading...

    What we see is that xSUSHI/USDT users on average withdraw a lot less collateral than users in the LINK/USDC and xSUSHI/FEI pools.

    Honestly, I am glad people came out of their positions by using LINK as collateral after looking at the price action against ETH (opinion).

    Summary

    In this investigation, we looked at the following. 0. Which Kashi pools have the all-time volume?

    1. How many people are borrowing this pair at the moment?
    2. How much collateral has each user added to the pair?
    3. How many users have already partially paid their loans?

    What we came out with is an understanding of which pools have the most Volume going through them, what is the average value-added and removed as collateral as well as which ones have the most usage in terms of the number of transactions.