Core functionality
Equilibrium is a fully on-chain liquidity management framework. The core of the Equilibrium framework consists of a bundle of smart contracts that govern how users interact with Equilibrium:
Positions contract
The position contract stores a user’s liquid digital assets in a unified pool, allowing for the management of this pool with help from on-chain governance. Equilibrium enables a family of EOSIO native assets whose values are managed using a stability mechanism. These assets are backed by a reserve of liquid digital assets supplied by users. The first stablecoin is EOSDT, pegged to USD. The positions contract also sets the logic for a user’s position management. It stores the framework’s global risk parameters, which specify how the system behaves, and governs the position creation process and a user’s position interactions.
Governance contract
Equilibrium uses an on-chain governance mechanism to manage and upgrade aspects of the framework that reside in the Equilibrium Core Contracts.
Equilibrium’s global risk parameters are configured by a governance mechanism, which means that NUT holders get to vote on proposals to change the framework’s parameters. If the majority agrees on new parameters, those become the norm.
Another important aspect of the Governance contract is the ability of NUT token holders to direct the liquidity pool to additional revenue streams available inside the EOS ecosystem, including (but not limited to): EOS REX resource lending, EOS block producer voting, and profit sharing.
Last but not least: the Governance contract allows NUT token holders to create proposals and vote on them for effective decentralized autonomous management of the entire framework.
Rates contract
The Equilibrium framework provides access to real-time market prices thanks to its rates smart contract. Any third party account or smart contract can subscribe to the price feed and receive timely updates required for business logic. Outside of accurately knowing collateral prices for risk management, the Equilibrium framework needs relevant prices for the NUT utility token to calculate the corresponding fees within the framework.
The Equilibrium framework works with Oraclize (now called Provable), Delphi Oracle, and Liquid Apps oracles to obtain timely market data on-chain. The system uses three different oracles for redundancy and calculates the median rate based on the data provided by these oracles. The median value is a final reference price used in all of the on-chain calculations.
Liquidator contract
Normal framework operations are only possible when each position’s collateral-to-debt ratio is above the liquidation ratio (critical_ltv parameter on positions contract currently set at 130%). When checking position safety, the external reference price is used in order to establish the USD value of the collateral, while the USD par price is used to price the EOSDT liability. Thus, position safety is assessed in terms of USD at a target price 1 EOSDT = 1 USD. By liquidating positions that fall below the liquidation ratio, the system can ensure that the USD value of collateral backing circulating EOSDT remains within determined parameters. Liquidated positions accrue balances on the Liquidator contract.
Collateral balance accumulates on the liquidator contract from positions that get margin called. This collateral is sold in exchange for EOSDT — a so-called “collateral auction.” Collateral auctions cover EOSDT liabilities originating from liquidated positions. The Liquidator contract sells EOS collateral at a discount from the reference price to incentivize EOSDT liability liquidation. It's a fixed price sell-off rather than an auction.
All interactions with the Liquidator contract are done via transfers from any EOS account:
Transfer EOSDT when there is non-zero "bad debt" on the liquidator contract and receive EOS collateral at a 3% discount.
Transfer NUT when nut_collat_balance is non-zero to buy out excess EOS collateral at a 6% discount.
Transfer EOS when surplus_debt is non-zero (non-zero equilibrium fee, which is not the case right now) on the liquidator contract to buy out EOSDT at a 3% discount
The killer features of the Equilibrium framework are its protection of EOSDT-to-USD parity and its ability to maintain a high level of confidence in the framework’s responsiveness to market events.
Reviewing the main two protections in place:
the EOSDT generator needs to post sufficient EOS collateral to fulfill at least 170% of the generated EOSDT value (measured at 1 EOSDT = $1 USD).
Assuming no margin calls, liquidations or adverse market action, the 170% requirement theoretically protects EOSDT’s $1 parity from a 41% maximum drawdown event (i.e. 70% less collateral).
The EOSDT generator is heavily incentivized to post more than the minimum 170% collateral, or else there is a material risk of auto-liquidation with a 20% liquidation penalty. If the EOSDT generators can’t post enough, they can alternatively repay the position’s original amount voluntarily. Either way, the system’s collateral-to-position ratio benefits from a natural resistance level. In other words, the average EOSDT generator should display strong risk-averse behaviors against collateral drops that would exceed the resistance level.
To avoid the liquidation penalty, a participant would post in excess of 50% or 100% of the minimum required collateralization ratio.
In the following analysis, we consider a mono-currency EOS collateral framework and its parameters, since EOS is the initial collateral asset supported by Equilibrium at the time of writing.
Insight on Equilibrium participant behavior: the DAI-ETH case
Equilibrium is a new project with no historical data yet. EOS price history is similarly only available since the January 2018 launch of EOSIO. In order to mitigate our lack of EOSDT and EOS data, we have modeled data on the comparable DAI stablecoin (with ETH as collateral) to gain insight on how EOSDT participants will behave. EOS warrants a conservative approach to our analysis because its returns have a much higher risk profile.
Let’s start with a few simple observations of the collateral to position ratio:
Like EOSDT, the DAI has also a penalty fee for auto-liquidation around 15%. The correlation between ETH returns and DAI Collateral to debt ratio movements unsurprisingly exceeds 65% for daily movements and 75% for weekly movements: the ETH collateral to debt ratio movements highly correlate with the ETH returns.
It furthermore looks like the 250% ETH collateral to debt ratio could be the natural resistance level that we mentioned earlier. The collateral to debt ratio hardly goes below this level.
The 250% resistance level surprisingly does not reduce the overall risk of the collateral to debt ratio, as measured by volatility and higher order moments.
An analysis of the collateral asset: the EOSDT-EOS case
The EOS daily log-returns essentially display most of the characteristics seen in stocks and equity indexes. By this we mean,
Absence of autocorrelations (see figure [3]).
Heavy tails (kurtosis > 3): EOS distribution is leptokurtic with fat tails.
Volatility clustering (see figure [4]): Autocorrelation in the absolute returns process is generally a sign that high volatility returns tend to cluster: volatility is stochastic. If we have an extreme absolute log-return, there is a high probability that the absolute log-return on the following day will also be high.
Slow decay of autocorrelation: decay is typically a power law of time. Slow decay is a sign of long-range memory for the absolute or squared returns process: EOS volatility can be projected with better results if the model learns from the long history of volatility behavior (see the rough volatility model and its calibration on historical intraday volatility by Gatheral and Rosenbaum, for example). EOS’s limited history doesn’t let us conclude for significant correlations above order 10 (correlation of absolute log-returns with 10-day lagged absolute log-returns), as shown by the autocorrelogram, but more investigation in that direction is warranted.
Accounting for stylized facts around logarithmic EOS returns, we propose a framework using an intuitive and conservative approach similar to Jurek’s.
Our objective is to determine a measure of crash risk, and in fine, a reasonable liquid portion of the total collateral that is required to protect Equilibrium from a crash. Let’s assume here that the liquid portion can be sold instantly on the markets, without friction. Our concern is to make sure that there’s enough collateral available to be sold. The proceeds of the sale should at least cover the generated EOSDT value (and potential penalties: 20% of the current position).
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https://equilibrium.io/en
sources :
https://equilibrium.io/en
https://medium.com/equilibrium-eosdt