The definitive guide for Liquidity Providers on Voltz Protocol.
Voltz Protocol is a non-custodial automated market maker for interest rate swaps. The AMM is split into two core components; a vAMM that is used for price discovery only and a Margin Engine that allows traders and LPs to trade with leverage.
In terms of LPing, the vAMM utilizes concentrated liquidity concepts from Uniswap v3. This means LPs deposit liquidity within tick ranges. However, relative to Uniswap v3, there are a few key differences:
LPs collect fees every time a trade is made with their liquidity. This means LPs generate the most fees where there is balanced trading activity of VT and FT positions, since the positions keep netting out such that the LPs liquidity can go back into the vAMM to generate more fees.
This means the following variables positively impact LP returns:
As explained in detail in the litepaper, this means LPs returns are driven off the following formula:
Initially, stablecoin pools will have a fee parameter of 𝞴 = 0 (i.e. none of the LP fee will go to the protocol treasury) and 𝞬 fees, the LP fee, of 0.003 (i.e. 30bps). These fees will be built out per pool in the future, with any changes communicated well in advance.
These fee parameters were designed to give LPs sufficiently high fees to incentivise providing funds, whilst reducing the risk to liquidation and funding losses, as well as effects of excessively high leverage. When considering alternative fee parameters, it was important to balance the expected LP APYs, which are positively impacted by higher fee parameters, with the negatively-impacted trader APYs for the same higher fees. Comparisons between the LP and VT APYs, assuming 25% of liquidity is traded per day (consistent with the typical trading volume of Uniswap) are summarized below, as a function of the leverage provided. To strike a balance between LP and trader APYs under a variety of leverages, 𝞬 = 0.003 (i.e. 30bps) is seen as an effective compromise, offering strong returns for both LPs and traders in the platform.
Analysis on these parameters will be ongoing.
In order to analyze the returns of liquidity providers, we have run a few simple simulations. Before we proceed to the simulation results, it is important to note that we need to make a few assumptions.
We assume that the proportion of LP notional traded per day is 25%. This is based on Uniswap v3 trading data. Additionally we assume the liquidity provider has entered into a 60 day IRS pool as soon as it is initiated.
We also assume the fee factor (gamma) is 0.30% (of time-scaled notional). To be conservative, we will assume 20x leverage. Finally, we assume an ideal case scenario where all of the LP margin is recycled, meaning that all variable and fixed cashflows are continuously netted out by VTs and FTs consuming liquidity along the fixed rate range of the LP.
A critical consideration for LPs is the fixed rate range within which they are providing liquidity. An ideal case scenario is where the fixed rate range is aligned with the range that is one or two standard deviations away from the historical equilibrium APY in the underlying yield-bearing pool in order to ensure IRS trading activity happens within the LP’s fixed rate range to capture fee income.
For example, if we wanted to capture fee income from trading activity around 2020-12-25 in the plot below, we would set the range to be around 2% and 20%.
Using the assumptions above - of 20x leverage, 25% of LP notional traded per day, and 100% recycling - we can generate the following plots for LPs.
The plot below depicts the Cumulative Fee Income from a margin deposit of 100 Dai, we can see that the cumulative P&L is increasing over the entire term of the IRS pool. However, the rate of P&L increase starts to decline closer to maturity. This is driven off the fact the LPs fee is scaled based on time to maturity. In this scenario, the LP would generate 55% APY.
Below, we added a few additional plots that show the relationship between LP APY and a few variables of interest. Plots 2 and 3 show the relationship between LP APY and the proportion of notional traded and leverage respectively.
Whilst LPs have the ability to generate significant APYs through Voltz Protocol, they are also exposed to risks. Due to single-asset LPing, there is no risk of impermanent loss. However, there are the following risks:
When LP notional is used by a trader it is momentarily locked into a trade. For example if a FT uses the LPs margin, then the LP effectively becomes the VT on the other side of that trade. In an instance where a VT comes in and trades the same position, it nets out and the LPs margin goes back into the AMM to keep collecting fees. This is the process of Margin Recycling explained above.
However, LPs are exposed to a risk described as “funding rate risk” where a corresponding trade never takes place to net out the position. In this instance, the LP will remain locked into a swap until a trade arrives to net it out, or until the end of the term.
If an LP is locked into a swap, the fixed rate of the trade will be known, but the variable rate will move according to the underlying variable rate of the pool (e.g. cDAI). There is a chance this variable rate moves against the LPs position, meaning the LP would be paying out more than their receiving. There are two scenarios where these negative cash flows can arise:
In this scenario the worst case cash flows for the LP are bounded by:
This is reflected in the following formula for a VTs cash flow (assuming a 60 day pool):
Cash Flow = margin*leverage*(variable APY - fixed APR)*(60/365)
For the purpose of loss modeling we’ll assume the margin is 1 and leverage is 1. If the LP deposits liquidity in a low fixed rate range, where the rate paid out is 1% on average, then their loss is bounded to 1%*(60/365) = 0.16%.
These losses would change as the leverage increases and as the delta between the fixed rate paid vs. variable rate receives increases. This is shown below, where we assume a 60 day term and a margin of 1:
In this scenario the worst case cash flows for the LP are bounded by:
This is reflected in the following formula for a FTs cash flow (assuming a 60 day pool):
Cash Flow = margin*leverage*(fixed APR - variable APY)*(60/365)
Potential LP P&L can be modeled by looking at the delta between the Fixed APR and Variable APY and the leverage taken. This is shown below, where we assume a 60 day term and a margin of 1:
As with Traders, LPs deposit margin to create notional that goes into the vAMM. This means LPs can be exposed to liquidation risk, since they’re taking leverage. Importantly the initial margin requirement is always higher than the liquidation threshold, meaning once LPs have deposited margin they can then continue calling the Voltz Protocol SDK to analyze how close their position is to the liquidation zone. There are then two scenarios where a liquidation can occur:
Liquidations occur differently for these two scenarios.
In the first, this works the same as a VT of FT liquidation. A liquidator bot is able to liquidate the LPs position by triggering an unwind and takes a proportion of the LPs margin as a reward.
In the second, a liquidator bot can burn the notional of the LP in the vAMM and then take a proportion of the LPs margin as a reward. At this point any unnetted (i.e. un-recycled) trades would also be unwound as above. This second scenario means the LPs notional is removed from the vAMM so it can’t be traded, but the margin is left untouched except for the LPs reward that’s taken.
LPs can monitor how close their margin is to the liquidation threshold by calling the Voltz Protocol SDK and pulling the liquidation margin requirement and comparing that to their current margin.
Just like in protocols like Aave or Compound, the liquidation penalty (or the reward of the liquidators) is dependent on the underlying asset / yield-bearing pool. For the low volatility stablecoin pools, the liquidator penalty is 5%, which is in-line with the penalties in stablecoin lending pools on the money market protocols.
Acting as an LP can also enable sophisticated traders to implement the following strategies:
We’ll provide further analysis of these strategies in due course.
Please see the user interface guide for instructions on how to provide liquidity via the app interface.