Protocol risks

Volatility Risks

Affects: Сritical LTV

Enjoyoors needs a robust measure to identify collateral portfolio constituents' losses in the worst-case scenario. Enjoyoors uses statistical bootstrap to gauge the volatility risk and to calculate critical LTV levels (discounts):

• Generate return distribution of the collateral asset in question.

• Approximate distribution parameters (mean, variance, skewness, jumps, etc.)

• Simulate N return paths using estimated parameters.

• Calculate expected tail loss: take an average worst 1% return from all simulations.

• Use this value scaled with the relevant period to calculate critical LTV levels and confidence bands.

Correlation Risk

Affects: relative collateral portfolio weights and supply limits

Deciding what assets to accept as collateral is a portfolio allocation and a portfolio optimization problem. If Enjoyoors protocol manages to collect and maintain a well-diversified portfolio of collateral assets that will yield the desired risk/return characteristics.

Correlation helps identify the right collateral portfolio weights. Unfortunately, calculating and predicting correlations is hard. There is also plenty of academic evidence that the naive equal weighting is pretty hard to beat. We’re also faced with limited or absent data for correlations calculation. Despite all the pitfalls described above, it’s always good to know how well-diversified your portfolio is. To gauge this, Enjoyoors calculates a portfolio diversification multiplier and sets an objective to maximize it.

Consider a simple example of two asset portfolios where the assets are perfectly correlated and have the same annualized volatility of 100%. The portfolio volatility will be the same as the volatility of its constituents: 100%, and there is no diversification benefit; the multiplier is 1.

If the correlation between two assets falls to 0.5, the resultant portfolio volatility will be 86.6%, and the diversification multiplier will be 100% / 86.6% ~ 1.15. Reducing correlations even further to 0.0 yields portfolio volatility of 7.07% and a multiplier of 1.41.

You get the idea: the more the collateral portfolio is diversified, the less risk (volatility) it has. The diversification multiplier is then calculated concerning the volatility target (which, in the case of Enjoyoors, is the volatility of the underlying synthetic).

Liquidity Risk

Affects: critical LTV, collateral supply limits.

Liquidity risk is pretty straightforward to understand: The less liquidity there is on the venues where the collateral asset is traded, the higher the price impact will be when Enjoyoors manage asset positions (for example, when rebalancing a portfolio, or liquidating part of the position to meet LTV thresholds). To gauge the market liquidity, Enjoyoors has developed an in-house scoring system that calculates the real-time liquidity score of an asset, taking into account the following factors:

• TVL: Combined liquidity (TVL) on all available AMMs and DEX-es where the asset is traded.

• CEX presence: Presence or absence of liquidity on centralized exchanges.

• Liquidity depth: 2%, 5%, 10% depth on both DEXes and CEX-es

• Locked liquidity share: how much liquidity on DEX-es is locked due to LP staking.

• Liquidity profile: any potential skew or poor liquidity on the bid side should be considered when calculating the final liquidity score.

All assets are ranked based on the above metrics and are then assigned a final score between 0 and 100. 0 is no liquidity or worst liquidity conditions, while 100 roughly corresponds to an ability to immediately realize $1M of the asset with less than 2% market impact.

Exposure Risk

Affects: relative collateral portfolio weights and supply limits

This risk is closely tied to Liquidity risk, and broadly speaking, it gauges what the supply limits on all of the collateral assets supported by the Enjoyoors protocol should be. On a very basic level, it doesn’t make sense to configure Enjoyoors pools to allow for 1B of collateral assets in asset A if aggregate combined liquidity on all AMMs in asset A is 500M. Instead, the supply limit should be a fraction of the 500M, not the out-of-touch 1B assets.

Qualitative Risk

Affects: collateral asset market volatility and the critical LTV (indirectly).

Enjoyoors uses public and proprietary information sources about each company behind each collateral asset to assess its intangible quality. Again, we built a proprietary ranking model that helps us compare different assets using hardly quantifiable metrics. Here are some of the factors we consider, among others, when building our qualitative risk-scoring model:

• Investor list, round information, valuations.

• Asset holdings distribution - number of holders and strong hands.

• Social media score (like X score, number of influential and KOL followers, etc.)

• Centrality scores and connection rankings.

• Average engagement rates on social media.

• Sentiment analysis and discord activity.

• Competition and SWOT analysis, similarity score in relation to competitors.

• Legal and regulatory compliance and obstacles.

Other Protocol Risks

Other risks of the Enjoyoors protocol may be broken down to the following:

Technology risk: refers to the potential for financial or operational loss due to flaws, vulnerabilities, or malicious actions within any part of the Enjoyoor’s technology (smart-contracts, appchain, relayers). To mitigate these risks Enjoyoors will perform multiple audits of its core tech, as well as integrate with real time threat monitoring services which will be able to pause Enjoyoors’ vaults in case of malicious actions.

Oracle and price manipulation risk: Inconsistent or corrupt pricing information could lead to unintended synthetic supply shock or the insolvency of certain markets. Enjoyoors integrates 2 oracle providers: PYTH and Chainlink, as well as organizes direct market feeds from a number of CEXes and DEXes. All of these price feeds are then medianized and monitored real time for outlier price detection. The failure of any single one and even several of them simultaneously will not materially affect the Enjoyoors protocol.

Synthetic supply shock risk: Big chunk of gigaAsset supply entering the market in a short period of time could affect its peg. This could happen due to a major slashing event, liquidation of the whale position on the lending protocol, or just because a malicious actor decided to attack the stability of Enjoyoors’ gigaAsset. Since Enjoyoors protocol controls gigaAssets’ circulating supply - it can decide how and on what terms to bootstrap the Сurve pool (making sure that substantial synths supply chunk in the pool is controlled by the IPA). Additionally, Enjoyoors governance can limit liquidity exposure to certain protocols to cap the amount of potential gigaAsset circulating supply entering the market.