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Trading Strategies
Vault-based protocols pool your funds inside a standardized structure so the trading strategy can deploy them. Funds remain locked for a set period known as the "epoch." Our core product offering is the following vaults:
- ETH++ (Arbitrum);
- ARB++ (Arbitrum)
The following vaults will be added over time:
- GM (Arbitrum)
- USDC++
- GLP++ (Avalanche)
Each vault uses a different trading strategy to capitalize on different market inefficiencies and expose funds to varying degrees of risk.
All strategies adopt the same theoretical principles:
- Identify drivers of market change;
- Build signals that capture those drivers;
- Turn those signals into positions;
- Risk-manage the positions.
Quantitative signals are generated from QV-Lab machine learning/modeling expertise. Human traders then filter and structure them qualitatively to extract optionality/exposure at a discount given the inelastic behaviors of end users of options (e.g., convenience yield/barriers to entry). Thus, D2.Finance operates a hybrid model combining quantitative and qualitative inputs.
D2.Finance applies sophisticated risk management procedures that consider ETH's price, size, volatility, liquidity, and inter-relationships with other cryptos.
Last modified 2mo ago