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30. WETH Owed
Jun 22, 2021 - These are the largest outstanding positions in the WETH-USDT pool with WETH owed to the position owner. The largest amount of WETH owed of these positions is ~2.5 WETH.
![40. [Super Hard] Impermanent Loss Dashboard](https://res.cloudinary.com/dsr37ut2z/image/upload/f_auto,q_auto,w_300/assets/backgrounds/dashboard-bg.png "40. [Super Hard] Impermanent Loss Dashboard")
40. [Super Hard] Impermanent Loss Dashboard
Aug 5, 2021 - Impermanent Loss in the context of Uniswapv3 is broadly defined as the dollar-denominated losses incurred from rebalancing positions or otherwise withdrawing liquidity at lower USD prices than supplied. The main question is how much price risk are the LPs exposed to when deploying capital. In this scenario we can compare how the portfolio would have performed if the LPs had HODLed instead of deploying capital. This does not include accrued but uncollected fees as that will have to follow in further analysis.
29. WETH - USDT Average Liquidity
Jun 22, 2021 - In the past 7 days, ~$3-85M liquidity was added to the WETH-USDT pools per day, with an average of 22.8M. In the same period ~$5-83M liquidity was removed from these pools per day, with an average of 22.68M.
Uniswap v3 Capital Efficiency (#18)
Jun 8, 2021 - The 5 largest v3 pools are USDC-WETH 3000 60, USDC-USDT 500 10, WBTC-WETH 3000 60, WETH-USDT 3000 60, UNI-WETH 3000 60. These are not the same as the 5 largest pools in v2, so we will look at the 5 largest v3 pools to give a common frame for comparison. We can define capital efficiency as $ of trade volume per $ of TVL. All 5 of these pools have been more capital efficient in v3 in the last 30 days, but this is most drastic for the USDC-USDT 500 10 pool (.05% fee tier). It is somewhat difficult to reason about the degree of concentration of capital, but one of the most naive metrics is to rank LP positions by the min and max price bounds of their tick range, taking the total amount of liquidity into account. Then, using a running tally of liquidity across these positions it is possible to produce a relationship between a widening lens of price spread inside of which liquidity is provided vs the % of total liquidity within that price spread. Another measure that could be used is Gini coefficient.
Uniswap 27. Strategies to Maximize ROI
Jun 15, 2021 - The most naive approach to identifying the best pools to supply in would just be to grab the highest volume pools on uniswap.info. A slightly more nuanced approach is to adjust these volumes by fee tier. Even better yet would be to divide by average TVL to determine a basic functional ROI computation. This then begs the question of what time scale to look at for the average values described above. that answer is partly dependent on the rebalancing strategy for the LP. If rebalancing more frequently it makes more sense to look at a shorter time scale (eg. 7 days) and if providing liquidity more passively then a longer time scale might make sense (eg. 30 days).
Analysis of liquidations
May 25, 2021 - This dashboard shows borrows and liquidations over time as well as liquidations as a percent of borrows broken down by asset. Liquidations generally represent a very small amount of the overall borrow value. There was a period of large liquidations on UNI, WBTC, and a few other tokens in early 2021. There is rarely ever more than 6% of any token supply that is liquidated on any given day, except for a few outlier days, which still never seem to exceed 30% of the overall borrow. Large percentages of the overall borrow supply do represent a very volatile lending market which has its risks. However, the larger risk is represented by the % of circulating token supply that these liquidations represent as the potential for illiquidity or impermanent market impact are the more significant concerns.
Analysis of Capital Utilization Ratio
May 25, 2021 - Borrow and supply volumes consistently increased heading into 2021. LTV has been remarkably consistent for Compound since late 2020. Though this has slightly decreased in the first part of 2021, it may be trending back up. It seems that tracking the rise of cryptoasset prices users actually pulled back on leverage indicating more of a risk-off mentality. This is most likely due to an unwillingness to pursue leverage with frothy prices as a result of expectations of downward correction. Following the May 19th crash, leverage-seeking behavior resumed.