Mirror.One is a trading exchange where you can trade assets that replicate returns of real -world assets. Mirror architecture is built to be a self-sustaining ecosystem. In the initial phase, there are two levels of liquidity pools — master reserve pool and each asset-token liquidity pool. The level of liquidity is de-coupled with the pegged-pricing mechanism. Unlike Uniswap, where liquidity levels are used for price discovery.
The interaction of master reserve pool and asset-token liquidity pool is rules-based:
· All funds from the sale of Mirror Token are deposited in the master reserve pool
· All transaction fees from trading pairs goes in the master reserve pool.
· Each asset-token is a liquidity pool has a dedicated self-sustaining liquidity pool
· For each asset-token pair, traders trade directly with the smart contract governed liquidity pool
· During periods of deficit in liquidity in the asset-token liquidity pool, the master reserve pool will fund the asset-token liquidity pool temporarily. When the master reserve pool is called for funding — an equivalent amount of Mirror tokens is burnt
· During periods of excess liquidity in the asset-token liquidity pool, all excess liquidity from the asset-token liquidity pool will flow to the master reserve pool. This step allows to keep sufficient liquidity in the individual asset-token pool allowing for price movements upto three standard deviations away from the closing price. Master reserve pool enables management of liquidity across multiple asset- token liquidity pools.
Excess/Deficit liquidity is defined as follows:
aL — [(aQ x aP) + 3σ]
aL = Asset-Token Liquidity level
aQ = Asset-Token Quantity currently in circulation
aP = Asset-Token price
σ = Standard deviation of daily returns of the asset
As the protocol adoption grows, incidences of low liquidity should reduce to zero. We use a predictive model to balance liquidity levels and minimize events of low liquidity. Greater protocol adoption will give us access to trading data, allowing us to implement machine-based learning models to improve how we define excess or low liquidity.
This self-sustaining liquidity protocol eliminates the need for centralized management as the interaction between asset-token liquidity pool and master reserve pool is contractual and rules based. It allows us to balance the liquidity levels through ebbs and flow and enables decoupling of liquidity and price of the asset.
The existing two layered liquidity protocol will transition into a multi-layered liquidity pool gradually as the adoption of the platform grows. Additional layers will be added between master reserve pool and individual asset-token liquidity pool to further diversify away any asset-class related idiosyncratic risks to make the overall protocol more secure.
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