[SLP-USDC-ETH] Collateral Onboarding Risk Evaluation

Legal Disclaimer : This communication is provided for information purposes only. The views expressed here are those of the individual quoted or who present said materials and are not the views of Maker Foundation (“Maker”) or its affiliates. This communication has been prepared based upon information, including market prices, data and other information, from sources believed to be reliable, but Maker has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation. This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any digital assets and the use of finance-related terminology are for illustrative purposes only , and do not constitute any recommendation for any action or an offer to provide investment advisory services. This content is not directed at nor intended for use by the MakerDAO community (“MakerDAO”), and may not under any circumstances be relied upon when making a decision to purchase any other digital asset referenced herein. The digital assets referenced herein currently face an uncertain regulatory landscape in not only the United States but also in many foreign jurisdictions, including but not limited to the UK, European Union, Singapore, Korea, Japan and China. The legal and regulatory risks inherent in referenced digital assets are not the subject of this content . For guidance regarding the possibility of said risks, one should consult with his or her own appropriate legal and/or regulatory counsel. Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any decision. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others.

  1. Summary Proposed Risk Parameters
  2. Overview
  3. Metrics and Analysis
  4. Risk Parameters

Summary Proposed Risk Parameters

Stability Fee: 5.5%

Liquidation Ratio: 125%

Debt Ceiling: 1 million DAI

Cut: 0.995

Step: 125 seconds

Buf: 1.15

Cusp: 0.6

Tail: 215 minutes

Chip: 0.1%

Tip: 300 DAI

Ilk.chop: 13%

Tolerance: 0.7

Ilk.hole: 1m DAI

Dust: 5000 DAI

Overview

Protocol Summary

Sushiswap is a fork of Uniswap v2 with few slight changes such as introduction of governance token and its tokenomics. At the time - late August 2020, Uniswap did not have a governance token which could be rewarded for “liquidity mining” and incentivisation of protocol usage; this instance enabled opportunity for “vampire mining”, which aimed to shift current asset liquidity used in Uniswap to the Sushiswap - the event was seen as greatly successful.

Initial main developer known as Chef Nomi pulled a “rug pull” on the community where he withdrawn his SUSHI/ETH liquidity and cashing it out for ether; the situation was later resolved with the help of Sam Bankman-Fried who managed to return the protocol to the community, via establishing a multi-sig with well-known crypto community individuals as signers, Chef Nomi also returned the funds to the projects treasury.

Sushiswap as fork of Uniswap is using the same automated market maker (AMM) methodology with the x*y=k formula to quote prices. The model relies on market depth being constructed from the pooled liquidity and market agents making swaps with it, where price slippage is relevant to the swap order size and the size of the pooled liquidity. Liquidity providers known as LPs are earning trading fees and are subject to “liquidity mining” rewards from the protocol, but are exposed to “impermanent loss” which is loss which can occur after the pooled assets fluctuate in price relative to the value of asset if they would not be deployed into the pool at all. In general, the accrued fees in combination with liquidity rewards often completely offset the impermanent loss.

Main difference between the two protocols is that Sushiswap distributed accrued protocol revenue from 0.3% protocol trading fees between LPs (0.25%) and xSUSHI token holders (0.05%). xSUSHI is received after depositing SUSHI into a pool called SushiBar; a way to distribute a portion of accrued revenue to token holders. In addition Sushiswap is continuously rewarding LPs with a liquidity mining program, where in addition to collected trading fees, suppliers are rewarded with the protocol token SUSHI.

Sushiswap governance works via voting, where votes are in the form of SushiPowah, which is a voting metric and works as followed; each SUSHI in the SUSHI-ETH pool is worth 2 SushiPowah and each SUSHI held via xSUSHI is worth 1 SushiPowah. Votes are managed on snapshot.page, quorum of at least 5 million SushiPowah is required and the multisig signers mentioned previously implement the changes into the protocol.

SLP-USDC-ETH is the Sushiswap LP (SLP) token consisting of USDC and ether; currently it is the third largest pool by liquidity in the protocol, holding $332M in assets, which means there is approximately $166M worth of both assets deposited. This is currently one of the largest USDC/ETH on-chain pools by absolute liquidity.

One important difference between how Sushiswap LPs will be implemented into MCD compared to Uniswap LPs is that prior will be using the CropJoin Adapter (SushiJoin), meaning that SLP collateral will be subject to liquidity mining rewards; SLP positions will achieve higher expected return compared to Uniswap LPs.

Metrics and Analysis

Trading volume on CEX & non-custodial venues

Sushiswap LP tokens (SLP) can be minted and redeemed from the pool contract with the underlying assets. There is essentially no trading of the SLP-USDC-ETH tokens themselves, so liquidity of LP tokens is best understood as a function of the liquidity of constituent assets. As an example, keepers can liquidate LP token positions by redeeming the token with the contract and then selling the underlying assets. An important thing to note is that due to the pricing mechanism used by AMM based venues, the real asset weights in the pool do not always reflect the target weight (in this case 50:50), which means that Keepers must take this into account when redeeming the underlying assets.

Token Distribution & Issuance Schedule

SLP-USDC-ETH tokens are created and redeemed via the Sushiswap pool contract, so the total supply of LP tokens depends on users’ decisions to enter or exit the liquidity pool. There are no centralized minting functions or other inflationary factors in token supply.

Token Deposits on Trading Venues and DeFi Exposure

SLP-USDC-ETH is not listed for trading on any centralized or decentralized exchange venues, as creation and redemption is available directly through the pool contract with no fees or slippage.

Vast majority of SLP USDC-ETH tokens (99.64%) are deposited into Sushiswap’s incentivized SUSHI farming pool - MasterChef Staking Pool.

Downside Risk

Because Sushiswap LP tokens are not traded independently, it’s not possible to check previous trading history to assess downside risks. But, the invariant function (y*x=k) allows for calculating drawdowns deterministically based upon the price performance of constituent assets. Details about LP returns can be found in Uniswap’s blog and this Medium post.

Assuming the price of USDC stays stable, a decline in the price of ETH will lead to a corresponding decline in the price of SLP-USDC-ETH from two factors: the loss in value of the 50% of the pool already held in ETH, and additional losses caused by “impermanent loss”.

SLP-USDC-ETH percentage loss = loss from existing holdings + impermanent loss

Loss from existing holdings = ETH percentage price change * ETH allocation (50%)

Impermanent loss = ((2 * sqrt(1 + ETH percentage price change) / (2 + ETH percentage price change)) - 1) * (1 + (0.5 * ETH percentage price change))

E.g. if ETH price suffers 50% percentage drop:

Loss from existing holdings = -0.5 * 0.5 = -0.25

Impermanent loss = ((2 * sqrt(0.5) / 1.5) - 1) * (1 - 0.25) = -0.043

SLP-USDC-ETH loss = -0.293

50% drop in ETH price leads to 29.3% drop in SLP-USDC-ETH value, assuming no change in USDC price and excluding any positive fees earned by LPs. The relationship between ETH and SLP-USDC-ETH price performance is shown below.

Source: Coinmarketcap, May 2021

Sushiswap has only been live since late August 2020, but based on the historical ETH price and Uniswap’s invariant formula, SLP-USDC-ETH would have experienced substantially fewer sharp drawdowns in price than ETH. The largest price drawdown would have been 33%, experienced on 12 March 2020 on the same day when ETH price fell 55%.

Source: Coinmarketcap, May 2021

Historical Fee Returns

Sushiswap liquidity pools earn a 0.25% fee from each trade. Over time, this income accrues to liquidity providers and helps counteract negative effects of impermanent loss. In addition, SLP token can be staked for additional SUSHI rewards, which are not equalized between pools and can also change over time based on what kind of liquidity and users protocol wish to attract more.

Average daily annualized fee earnings for SLPs were 23.63%. In addition, SLP collateral will be earning SUSHI rewards, which substantially increase their expected return. The return of SUSHI rewards is based on several factors, such as liquidity mining reward allocation to the pool, amount of capital in the pool, price of SUSHI and thus fluctuates; at the time of writing, annualized SUSHI reward for SLP-USDC-ETH was ~26%. The USDC-ETH pool has slightly higher trading activity compared to DAI-ETH pool which results in higher return from collected fees, but has lower SUSHI allocation for liquidity mining and thus results in slightly lower returns from that source. The two pools yield similar total returns.

Source: Sushiswap.vision, May 2021

Summary of Notable Risks

  • This collateral type is exposed to specific USDC related risks and with addition of SLP-USDC-ETH collateral we are increasing our exposure towards these specific risks.

  • SLP-USDC-ETH will suffer from impermanent loss when ETH experiences large moves. LP borrowers may have an incentive to repay their debt and remove liquidity during a large price decline, which would lower liquidity on the market which can increase slippage for other collateral types such as ETH or other tokens which are pooled together with USDC across markets.

  • Sushiswap governance can change SUSHI liquidity mining reward allocation, but this is a major pair so it is likely to remain.

  • The SLP collateral will be farming SUSHI rewards which is a novel type of vault due to additional functionality and present an additional smart contract risk.

Proposed Risk Parameters

Stability Fee: 5.5%

Liquidation Ratio: 125%

Debt Ceiling: 1 million DAI

Cut: 0.995

Step: 125 seconds

Buf: 1.15

Cusp: 0.6

Tail: 215 minutes

Chip: 0.1%

Tip: 300 DAI

Ilk.chop: 13%

Tolerance: 0.7

Ilk.hole: 1m DAI

Dust: 5000 DAI

We used the model from the Collateral Risk Assessment Guide here. As this collateral asset behaves very similarly to UNIV2USDCETH we propose a similar set of initial parameters with an additional premium on current stability fee of 1 percentage point as additional liquidity mining rewards offer higher expected returns for users and potentially more risk as there are additional complexities related to vaults collecting rewards. We usually recommend initiating a new collateral with a small debt ceiling, Uniswap LPs were initiated at 3m dai, but in this case we are introducing a new vault functionalities so we recommend even lower initial debt ceiling at 1m dai. Same recommendation was also made by other mandated actors such as the Oracles and Protocol Engineering team. The debt ceiling and other parameters will be adjusted after some time of testing. A link to our model specification with inputs and outputs can be found here. Auction parameters have been selected to mirror those for UNIV2USDCETH-A with smaller ilk.hole.

Data for graphics included in this report can be found here.

Lead Researcher: Marko Štemberger

Sources:

3 Likes