Yield Generation
Stasis employs multiple sophisticated mechanisms to generate stable yield while maintaining market neutrality. This document explains how the protocol creates value for users through various yield sources.
Primary Yield Sources
1. Funding Rate Arbitrage (Primary)
Mechanism
Hold short positions in perpetual futures
Collect funding payments from long position holders
Maintain delta neutrality through spot hedging
Yield Characteristics
Frequency: Every 8 hours (3x daily)
Stability: Historically positive in crypto markets
Magnitude: 5-15% annualized in normal conditions
Example Flow
1. Vault holds $1M USDC
2. Opens $800k short ETH perpetual position
3. Receives funding payment: $800k × 0.01% = $80 every 8 hours
4. Daily income: $80 × 3 = $240
5. Annual yield: $240 × 365 = $87,600 (8.76% on position)
2. Basis Trading (Secondary)
Mechanism
Capture price differences between spot and futures
Profit from convergence at settlement
Exploit temporary market inefficiencies
Opportunities
Contango: Futures trading above spot (profit from convergence)
Backwardation: Futures trading below spot (less common in crypto)
Volatility Events: Temporary dislocations during market stress
Risk Management
Limited exposure to basis trades
Focus on high-probability convergence plays
Quick position unwinding capabilities
3. Volatility Premium Capture (Tertiary)
Mechanism
Sell overpriced volatility through options strategies
Capture volatility risk premium
Maintain delta neutrality through dynamic hedging
Implementation
Limited options exposure
Focus on short-term volatility trades
Sophisticated risk management required
Yield Optimization Strategies
Dynamic Position Sizing
Funding Rate Responsive
def calculate_position_size(funding_rate, volatility, max_leverage):
base_size = vault_value * 0.8 # 80% base exposure
# Increase size when funding rates are high
funding_multiplier = min(funding_rate / 0.01, 2.0) # Cap at 2x
# Reduce size when volatility is high
volatility_discount = max(1 - volatility / 0.5, 0.5) # Min 50%
optimal_size = base_size * funding_multiplier * volatility_discount
return min(optimal_size, vault_value * max_leverage)
Market Condition Adaptation
Bull Markets: Increase exposure (higher funding rates)
Bear Markets: Maintain conservative sizing
High Volatility: Reduce leverage, focus on stability
Asset Allocation
Multi-Asset Approach
Target Allocation:
- ETH Perpetuals: 40-60%
- BTC Perpetuals: 30-40%
- Other Assets: 0-20%
- Cash Buffer: 10-20%
Selection Criteria
Funding Rate History: Consistent positive rates
Liquidity: Sufficient market depth
Volatility: Manageable price movements
Correlation: Diversification benefits
Timing Optimization
Funding Rate Prediction
Historical pattern analysis
Market sentiment indicators
Technical analysis signals
Machine learning models
Position Entry/Exit
Optimal timing around funding events
Market microstructure analysis
Liquidity-aware execution
Compounding Mechanisms
Automatic Reinvestment
Process Flow
1. Funding payments received → Vault value increases
2. Exchange rate improves → rSTS becomes more valuable
3. No user action required → Seamless compounding
4. Gas-efficient → No claiming transactions
Mathematical Model
Compound Growth Formula:
Final Value = Initial × (1 + Daily Rate)^Days
Example:
$1,000 × (1 + 0.0164%)^365 = $1,061.83 (6.18% APY)
Efficiency Advantages
vs. Manual Claiming
Gas Savings: No transaction fees for claiming
Timing Optimization: Reinvestment at optimal moments
Convenience: No user intervention required
vs. External Compounding
Capital Efficiency: No external protocol fees
Reduced Risk: No additional smart contract exposure
Immediate Reinvestment: No delays or slippage
Performance Metrics
Yield Measurement
Gross Yield
Gross APY = (Total Funding Earned / Average Vault Value) × 365/Days
Net Yield (After Fees)
Net APY = Gross APY - Management Fee - Performance Fee - Operating Costs
Risk-Adjusted Yield
Sharpe Ratio = (Net APY - Risk-Free Rate) / Volatility
Information Ratio = (Net APY - Benchmark) / Tracking Error
Efficiency Metrics
Funding Rate Capture
Capture Efficiency = Actual Funding Earned / Theoretical Maximum
Target: >90%
Delta Accuracy
Delta Accuracy = 1 - (Average |Delta| / Target Range)
Target: >95%
Cost Efficiency
Cost Ratio = Total Costs / Gross Yield
Target: <20%
Risk-Return Optimization
Risk Budgeting
Allocation Framework
Total Risk Budget: 100%
- Funding Rate Risk: 60%
- Delta Risk: 20%
- Operational Risk: 15%
- Liquidity Risk: 5%
Dynamic Adjustment
Increase risk during favorable conditions
Reduce risk during market stress
Maintain minimum safety buffers
Return Enhancement
Leverage Optimization
Optimal Leverage = f(Funding Rate, Volatility, Risk Tolerance)
Typical Range:
- Conservative: 1.5-2.0x
- Moderate: 2.0-2.5x
- Aggressive: 2.5-3.0x
Strategy Diversification
Multiple yield sources
Different time horizons
Uncorrelated strategies
Market Conditions Impact
Bull Market Characteristics
High Funding Rates: 15-50% annualized
Strong Performance: Above-target yields
Increased Leverage: Optimal conditions for scaling
Bear Market Characteristics
Lower Funding Rates: 3-10% annualized
Stable Performance: Consistent but reduced yields
Conservative Positioning: Focus on capital preservation
Sideways Market Characteristics
Moderate Funding Rates: 5-15% annualized
Steady Performance: Target yield achievement
Balanced Approach: Optimal risk-return balance
Future Enhancements
Strategy Evolution
Additional yield sources
Improved prediction models
Enhanced automation
Technology Improvements
Better execution algorithms
Real-time optimization
Advanced risk management
Market Expansion
New asset classes
Additional exchanges
Cross-chain opportunities
Next: Using Stasis