Here is what we are going to cover:
Impermanent loss mitigation mechanisms.
IL mitigation variables.
Liquidity depth - Slippage - Trade value correlation.
This article explores the variables that need to be considered in an ecosystem of AMMs when mitigating impermanent loss. The article provides intermediatory information on the actions of traders, AMMs, arbitrageurs, LPs, and liquidity depth and their effects on net profits and losses.
The main incentive for the users to supply liquidity is the incentives in the form of farm tokens and/or the fees generated from the swaps. These swap fees usually outperform the normal performance of the HODLing portfolio when the market is bearish or sideways.
One of the risks users face for providing liquidity is impermanent loss; IL is basically the loss that is equivalent to the upside gained on HODLing the token instead of providing liquidity. In other words, Impermanent loss is an opportunity cost that may occur while providing liquidity, due to the price shift of one asset of the liquidity pool, versus holding the assets.
If we were to examine or design a mechanism for IL protection, we need to consider different variables attached to the group of AMMs similar to a market of markets.
Participants:
LP: A liquidity provider is the one who provides liquidity for yield.
Trader: One who trades an asset for another asset.
Arbitrageur: One who balances the pool based on price difference among the market makers. Arbitrage is likely to be a profitable trade.
AMM: The market maker and the one who hosts liquidity pools.
Mechanisms:
Swap fees: A cut from swap trade between assets from the liquidity pool.
Arbitrage: The price difference between the same assets in different market makers or liquidity pools.
Incentives: Incentives can be from Swap fees and/or native protocol tokens.
Slippage: The price difference between the order price and execution price. The difference is created as one asset is getting scarce in the pool and a premium is charged to buy that scarce asset, this premium can be considered slippage. I call it the cost of capturing demand.
Impermanent loss: Impermanent loss is an opportunity cost that may occur while providing liquidity, due to the price shift of one asset of the liquidity pool, versus holding the assets.
Liquidity depth: Concentration of liquidity near the trading price.
Understanding concepts with real examples are fun; let us take an example where there are two liquidity pools Pool 1 & Pool 2, a trader trading 5% of the pool TVL, and an arbitrageur looking for an optimal trader to balance the pool and gain max profits.
We would look at what the net P/L looks like for LP, Trader, and Arbitrageur when the following sequence is performed in a market.
LP forms 2 liquidity pools with his/her total assets of $ 800,000 (ABC/USD) > a trader buys 5% of ABC from the Pool 1 > an arbitrageur balances the pool perfectly. The analysis would consist of the scenarios where the LP distributes his/her $ 800,000 between 2 pools in different proportions.
Scenario 1 Equal distribution of liquidity across both pools.
If we run the sequence with different pool compositions for comparison purposes something interesting comes out, here is the comparison view:
The impermanent loss stays the same regardless of the distribution of liquidity to the pools in the market provided the liquidity depth is the same across all the pools. [IL experienced in a pool without liquidity concentration = IL experienced in a pool with liquidity concentration / Liquidity depth.][Assumptions]
For the same amount of trade, a trader makes a loss due to slippage when a pool with less liquidity is chosen. [aggregators]
The cost of balancing the pools i.e. arbitrage is higher in the case where a trader experiences high slippage.
Arbitrageurs benefits if the trader trades in a high slippage environment/pool.
Trader benefits if they trade in a low slippage environment/pool
As slippage tends to 0, the arbitrage also tends to 0 (constant sum function). This is useful in the pools consisting of pegged assets.
Slippage is a huge contributing factor for the trader to choose a certain liquidity pool. To cater to low slippage, the AMM/protocol could source more liquidity or accumulate liquidity near the trading price. In both cases, the amount of slippage could be the same though the liquidity is not equal for both the pools, here is an example:
The slippage would be less in pool B than in pool A for the same amount of trade. The liquidity depth for pool B is 1.5x pool A near the trading price. Lower slippage for the same amount of liquidity has its own consequences. IL would be proportional to the liquidity depth for the same price post-trade.
Liquidity pool example ABC/USD at an exchange rate of $2000
Slippage is inversely proportional to the amount of liquidity and/or the Liquidity depth of the pool.
Impermanent loss is proportional to liquidity depth. The catch here is that it would require higher trade volume for distorting the pool to cause the impermanent loss.
Liquidity concentration can be a double edge sword when it comes to impermanent loss, as liquidity depth reduces the volatility in asset price. Everything depends on the type of assets in the liquidity pool and their correlation with each other.
If a liquidity pool relies on the balance of the asset for determining the price impermanent loss is hard to void and will persist. If a pool does not rely on the assets reserves for determining the price the impact of Il will be minimized as there will be no arbitrage opportunities and there won’t be a deficit in a single asset due to the arbitrage trading. This is explained further in the mechanism section.
Using native protocol tokens to make up for the impermanent loss
This is similar to taking money from the investors holding your protocol’s native token to square off the IL faces by the LPs
The tokens distributed for covering the IL are exposed to high selling pressure, and if there is not enough utility or buy pressure to balance the supply, the intrinsic value of the native token would drop.
Swap fees and Variable fees based on the volatility and the extent of the pool distortion
Variable fees act like a premium for a trader who wants to distort the pool in a single direction.
Variable fees can even act as a premium for trader trading in a volatile market.
These fees are more when a trade is meant to make the pool out of balance and the fees would be less when a trade is meant for rebalancing the pool.
This makes sure the distortion of the liquidity pool is minimized thus very minimal impermanent loss.
Limiting arbitrage
Using oracle for the price feed rather than relying on the assets in reserve to derive the price. The arbitrage is fully eliminated in this mechanism.
This mechanism can be combined with the variable fees based on distortion and volatility to make it more resilient to arbitrage.
The only drawback to this mechanism is that the overall market would be volatile.
For example, if there are only 2 pools in the whole Defi market for ABC/XYZ, Pool_A provides price feed to Pool_B. If a trader buys ABC from Pool_A the resulting price in Pool_A would be the price of an asset ABC across the market.
If both Pool_A and Pool_B relied on the price derived from the balance of reserve assets the price of an asset ABC would be less than the scenario described above due to arbitrage pool balancing.
Stay tuned! This was an introductory article going through the variables in the IL mitigation mechanisms. Protocols with impermanent loss protection will be covered and examined in the upcoming articles.
Thank you for reading 🙌.
You can provide the same value by sharing this article with your circle.
Subscribe! I write about interesting protocol mechanisms, insights, and analyses.
You can even contribute/support these articles by owning one ✌.
Here is what we are going to cover:
Impermanent loss mitigation mechanisms.
IL mitigation variables.
Liquidity depth - Slippage - Trade value correlation.
This article explores the variables that need to be considered in an ecosystem of AMMs when mitigating impermanent loss. The article provides intermediatory information on the actions of traders, AMMs, arbitrageurs, LPs, and liquidity depth and their effects on net profits and losses.
The main incentive for the users to supply liquidity is the incentives in the form of farm tokens and/or the fees generated from the swaps. These swap fees usually outperform the normal performance of the HODLing portfolio when the market is bearish or sideways.
One of the risks users face for providing liquidity is impermanent loss; IL is basically the loss that is equivalent to the upside gained on HODLing the token instead of providing liquidity. In other words, Impermanent loss is an opportunity cost that may occur while providing liquidity, due to the price shift of one asset of the liquidity pool, versus holding the assets.
If we were to examine or design a mechanism for IL protection, we need to consider different variables attached to the group of AMMs similar to a market of markets.
Participants:
LP: A liquidity provider is the one who provides liquidity for yield.
Trader: One who trades an asset for another asset.
Arbitrageur: One who balances the pool based on price difference among the market makers. Arbitrage is likely to be a profitable trade.
AMM: The market maker and the one who hosts liquidity pools.
Mechanisms:
Swap fees: A cut from swap trade between assets from the liquidity pool.
Arbitrage: The price difference between the same assets in different market makers or liquidity pools.
Incentives: Incentives can be from Swap fees and/or native protocol tokens.
Slippage: The price difference between the order price and execution price. The difference is created as one asset is getting scarce in the pool and a premium is charged to buy that scarce asset, this premium can be considered slippage. I call it the cost of capturing demand.
Impermanent loss: Impermanent loss is an opportunity cost that may occur while providing liquidity, due to the price shift of one asset of the liquidity pool, versus holding the assets.
Liquidity depth: Concentration of liquidity near the trading price.
Understanding concepts with real examples are fun; let us take an example where there are two liquidity pools Pool 1 & Pool 2, a trader trading 5% of the pool TVL, and an arbitrageur looking for an optimal trader to balance the pool and gain max profits.
We would look at what the net P/L looks like for LP, Trader, and Arbitrageur when the following sequence is performed in a market.
LP forms 2 liquidity pools with his/her total assets of $ 800,000 (ABC/USD) > a trader buys 5% of ABC from the Pool 1 > an arbitrageur balances the pool perfectly. The analysis would consist of the scenarios where the LP distributes his/her $ 800,000 between 2 pools in different proportions.
Scenario 1 Equal distribution of liquidity across both pools.
If we run the sequence with different pool compositions for comparison purposes something interesting comes out, here is the comparison view:
The impermanent loss stays the same regardless of the distribution of liquidity to the pools in the market provided the liquidity depth is the same across all the pools. [IL experienced in a pool without liquidity concentration = IL experienced in a pool with liquidity concentration / Liquidity depth.][Assumptions]
For the same amount of trade, a trader makes a loss due to slippage when a pool with less liquidity is chosen. [aggregators]
The cost of balancing the pools i.e. arbitrage is higher in the case where a trader experiences high slippage.
Arbitrageurs benefits if the trader trades in a high slippage environment/pool.
Trader benefits if they trade in a low slippage environment/pool
As slippage tends to 0, the arbitrage also tends to 0 (constant sum function). This is useful in the pools consisting of pegged assets.
Slippage is a huge contributing factor for the trader to choose a certain liquidity pool. To cater to low slippage, the AMM/protocol could source more liquidity or accumulate liquidity near the trading price. In both cases, the amount of slippage could be the same though the liquidity is not equal for both the pools, here is an example:
The slippage would be less in pool B than in pool A for the same amount of trade. The liquidity depth for pool B is 1.5x pool A near the trading price. Lower slippage for the same amount of liquidity has its own consequences. IL would be proportional to the liquidity depth for the same price post-trade.
Liquidity pool example ABC/USD at an exchange rate of $2000
Slippage is inversely proportional to the amount of liquidity and/or the Liquidity depth of the pool.
Impermanent loss is proportional to liquidity depth. The catch here is that it would require higher trade volume for distorting the pool to cause the impermanent loss.
Liquidity concentration can be a double edge sword when it comes to impermanent loss, as liquidity depth reduces the volatility in asset price. Everything depends on the type of assets in the liquidity pool and their correlation with each other.
If a liquidity pool relies on the balance of the asset for determining the price impermanent loss is hard to void and will persist. If a pool does not rely on the assets reserves for determining the price the impact of Il will be minimized as there will be no arbitrage opportunities and there won’t be a deficit in a single asset due to the arbitrage trading. This is explained further in the mechanism section.
Using native protocol tokens to make up for the impermanent loss
This is similar to taking money from the investors holding your protocol’s native token to square off the IL faces by the LPs
The tokens distributed for covering the IL are exposed to high selling pressure, and if there is not enough utility or buy pressure to balance the supply, the intrinsic value of the native token would drop.
Swap fees and Variable fees based on the volatility and the extent of the pool distortion
Variable fees act like a premium for a trader who wants to distort the pool in a single direction.
Variable fees can even act as a premium for trader trading in a volatile market.
These fees are more when a trade is meant to make the pool out of balance and the fees would be less when a trade is meant for rebalancing the pool.
This makes sure the distortion of the liquidity pool is minimized thus very minimal impermanent loss.
Limiting arbitrage
Using oracle for the price feed rather than relying on the assets in reserve to derive the price. The arbitrage is fully eliminated in this mechanism.
This mechanism can be combined with the variable fees based on distortion and volatility to make it more resilient to arbitrage.
The only drawback to this mechanism is that the overall market would be volatile.
For example, if there are only 2 pools in the whole Defi market for ABC/XYZ, Pool_A provides price feed to Pool_B. If a trader buys ABC from Pool_A the resulting price in Pool_A would be the price of an asset ABC across the market.
If both Pool_A and Pool_B relied on the price derived from the balance of reserve assets the price of an asset ABC would be less than the scenario described above due to arbitrage pool balancing.
Stay tuned! This was an introductory article going through the variables in the IL mitigation mechanisms. Protocols with impermanent loss protection will be covered and examined in the upcoming articles.
Thank you for reading 🙌.
You can provide the same value by sharing this article with your circle.
Subscribe! I write about interesting protocol mechanisms, insights, and analyses.
You can even contribute/support these articles by owning one ✌.
IL for older LP can be covered from the funds provided by the newer LP
This is Ponzi but can be a solution if well framed. This can be modeled with another mechanism where newer LP’s funds would surely recover but will need at least a bit of time.
IL for older LP can be covered from the funds provided by the newer LP
This is Ponzi but can be a solution if well framed. This can be modeled with another mechanism where newer LP’s funds would surely recover but will need at least a bit of time.
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DeFi Researcher & Data Analyst. Working with @LlamaRisk team.
DeFi Researcher & Data Analyst. Working with @LlamaRisk team.
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