Optimal weights of capital in liquidity pools according to their historical performance.
Optimal conversion between initial and final set of tokens on balance.
Risk-free maintenance of leveraged positions.
Growing collection of techniques to achieve the best performance across them.
Smart Contracts are passive, and we need many active components that initiate actions.
Our models are computation intensive and require external datasources which are often not available on determinist smart contracts or that require expensive oracles to connect to off-chain data sources.
Smart Contracts are visible to everyone on blockchain and have higher risk of hacks/attacks/front running bots.
We separate the data into two domains:
Real-time data & Historical data
We use historical data to automatically identify optimal historical metrics (performance of the pools, hedging health ratio) as a basis for automatic decision-making and “catch-up” the insights up to real-time. On the other hand, we use real-time data to update metrics and make real-time decisions.
Currently, we support 4 blockchains:
Ethereum
Avalanche
Polygon
Terra
Binance Smart Chain
We have numerous DeFi protocols supported on those blockchains – including, but not limited to:
Aave
Uniswap V3
Curve
Compound
Mirror
Convex
Frax
Our top priority is risk management. We started with stablecoins to offer our clients the best earnings with minimal possible risks.
We separate risks into the market (volatility) and counterparty (protocols) risks. We build complex models to eliminate market risks and have built manual processes to analyze counterparty risks.
While we can’t measure or predict counterparty risks, we can grade them by comparing them to each other. By doing so, we can estimate whether integrating new protocols will bring additional counterparty risk.