AI-Powered Infrastructure for Risk-Defined Yield
Requiem combines quantitative modeling, machine learning, and algorithmic execution to deliver sustainable yield generation with transparent risk management across digital asset markets.
Data, Metrics, Models—Before Yield
Every strategy deployed through Requiem undergoes rigorous quantitative analysis, stress testing, and AI-driven optimization before capital allocation. This is Requiem Labs' core mission.
Quantitative Research
Strategy development through statistical analysis and financial engineering
Backtesting Framework
Historical validation across multiple market cycles and volatility regimes
AI Model Training
Machine learning systems for market analysis and execution optimization
Algorithmic Execution
Automated deployment and continuous optimization of live strategies
AI-Assisted Strategy Management
Requiem employs multiple AI models working in concert to manage portfolios, optimize execution, and adapt strategies to changing market conditions—all within predefined risk constraints.
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1
Portfolio Allocation AI
Function: Determines optimal allocation weights across available strategies based on current risk regime, historical correlations, and user-defined risk constraints.
Input Data: Realized volatility, correlation matrices, strategy performance metrics, market liquidity indicators, risk zone parameters.
Output: Dynamic portfolio weights that maximize risk-adjusted returns while maintaining risk limit compliance. Rebalancing triggers when allocations drift beyond tolerance bands. -
2
Execution Optimization AI
Function: Optimizes trade execution across DEXs, bridges, and chains to minimize slippage, gas costs, and market impact.
Input Data: DEX liquidity depth, gas price predictions, bridge availability, historical slippage data, MEV risk indicators.
Output: Optimal routing paths, timing recommendations, and position sizing that minimize total execution costs. Includes MEV protection strategies where applicable. -
3
Risk Regime Detection AI
Function: Identifies shifts in market volatility regimes and correlation structures that require strategy adjustments.
Input Data: Cross-asset volatility surfaces, correlation breakdowns, liquidity metrics, funding rates, on-chain activity indicators.
Output: Regime classification (low/medium/high volatility) with confidence scores. Triggers automatic strategy weight adjustments when regimes shift beyond thresholds. -
4
Anomaly Detection AI
Function: Monitors protocol health, smart contract risks, and unusual market conditions that could impact strategy performance.
Input Data: Smart contract activity patterns, protocol TVL changes, exploit detection signals, governance proposals, liquidity concentration metrics.
Output: Risk alerts with severity classifications. Triggers automatic position reduction or exit when critical anomalies detected. -
5
Performance Attribution AI
Function: Analyzes returns to understand which factors (strategy selection, timing, execution) contributed to performance.
Input Data: Position-level returns, strategy benchmark performance, market factor exposures, transaction costs.
Output: Detailed attribution breakdown showing alpha vs beta, strategy contribution, and areas for optimization. Informs future model improvements.
What Our AI Does NOT Do
❌ Predict Prices: We do not attempt to forecast BTC to $100K or ETH to $10K. Price prediction is unreliable and unnecessary for our strategies.
❌ Override Risk Limits: AI operates within hard-coded risk constraints. No model can increase user risk exposure beyond documented parameters.
❌ Make Emotional Decisions: Models execute based on data and rules, never on fear, greed, or speculation.
❌ Guarantee Profits: AI optimizes probability-weighted outcomes but cannot eliminate market risk or ensure positive returns.
Comprehensive Risk Framework
Risk management is not an afterthought—it's the foundation of every strategy deployed through Requiem. Our framework operates at multiple levels to ensure user capital protection.
Strategy-Level Risk Controls
- Position Sizing: Maximum allocation per strategy to prevent concentration
- Stop-Loss Thresholds: Automatic exits when drawdown limits approached
- Liquidity Requirements: Minimum liquidity depth before position entry
- Correlation Limits: Maximum correlation to Bitcoin/Ethereum
- Leverage Constraints: Hard caps on borrowed capital ratios
Portfolio-Level Risk Controls
- Diversification Requirements: Minimum number of uncorrelated strategies
- Total Drawdown Limits: Portfolio-wide maximum loss thresholds
- Value-at-Risk (VaR): Daily monitoring of 95th and 99th percentile losses
- Stress Testing: Weekly scenario analysis across portfolios
- Rebalancing Rules: Automatic adjustments when drift exceeds bands
Protocol-Level Risk Controls
- Smart Contract Audits: Third-party security reviews before deployment
- Protocol Whitelisting: Only audited, battle-tested protocols used
- TVL Limits: Maximum capital per external protocol to reduce exposure
- Governance Monitoring: Tracking proposal changes in integrated protocols
- Emergency Circuits: Rapid exit mechanisms for critical situations
Risk Zone Parameter Examples
| Risk Metric | Conservative | Moderate | Growth |
|---|---|---|---|
| Maximum Drawdown | 8% | 15% | 25% |
| Annualized Volatility | 10-15% | 15-25% | 25-40% |
| Daily VaR (95%) | -1.5% | -2.5% | -4.0% |
| BTC Correlation | < 0.3 | < 0.5 | < 0.7 |
| Strategy Count | 8-12 | 6-10 | 4-8 |
| Expected Annual Return | 8-12% | 12-18% | 18-25% |
How Strategies Generate Yield
Transparency requires explaining exactly how returns are generated. Here's a breakdown of our primary strategy categories and their underlying mechanics.
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1
Cross-Chain Arbitrage
Mechanism: Exploiting price discrepancies for the same asset across different chains and DEXs. When ETH trades at $2,000 on Ethereum but $2,005 on Arbitrum, we buy on Ethereum and sell on Arbitrum.
Risk Sources: Bridge timing risk, gas cost variability, slippage on large trades, temporary liquidity constraints.
Expected Contribution: 3-6% annualized returns with low correlation to crypto market direction. Works in bull, bear, and sideways markets. -
2
Covered Call Writing (Options)
Mechanism: Holding crypto assets while selling call options against them to collect premium income. If ETH is at $2,000, we hold ETH and sell $2,200 calls, collecting premium while capping upside.
Risk Sources: Opportunity cost if asset rallies beyond strike price, premium erosion during extreme volatility, liquidation risk if using leverage.
Expected Contribution: 6-10% annualized premium income, best during sideways or mildly bullish market conditions. -
3
Delta-Neutral Market Making
Mechanism: Providing liquidity to order books or AMM pools while maintaining neutral exposure to price direction through hedging. Earn spreads and fees without directional bias.
Risk Sources: Impermanent loss in AMM positions, inventory risk during rapid price moves, toxic flow from informed traders, protocol smart contract vulnerabilities.
Expected Contribution: 5-12% annualized from fees and spreads, relatively stable across market conditions. -
4
Synthetic Index Construction
Mechanism: Creating exposure to custom indices (e.g., "DeFi Top 10") through derivatives rather than holding underlying tokens. Reduces gas costs and enables leverage/hedging.
Risk Sources: Tracking error vs benchmark, funding rate costs on perpetual swaps, counterparty risk on derivative platforms, rebalancing slippage.
Expected Contribution: Returns track underlying index + alpha from rebalancing efficiency (typically 2-4% outperformance). -
5
Funding Rate Arbitrage
Mechanism: Capturing funding rate payments on perpetual futures by holding offsetting positions. When funding rates are positive (longs pay shorts), we hold spot and short perpetuals.
Risk Sources: Basis risk if spot and futures diverge, exchange counterparty risk, liquidation risk if positions not properly balanced, funding rate reversals.
Expected Contribution: 8-15% annualized during high volatility when funding rates spike, lower during calm markets.
Technology Stack & Architecture
Requiem is built on battle-tested technologies and follows best practices for security, scalability, and reliability across the full infrastructure stack.
Smart Contract Layer
- Language: Solidity with extensive testing in Foundry/Hardhat
- Audits: Multiple independent security firms (OpenZeppelin, Trail of Bits)
- Upgradability: Proxy pattern with timelock governance for upgrades
- Gas Optimization: Optimized for cost efficiency without security compromise
- Multi-Chain: Deployed on Ethereum, Arbitrum, Optimism, Polygon, BSC, Avalanche
AI/ML Infrastructure
- Framework: Python-based using TensorFlow and PyTorch for model development
- Data Pipeline: Real-time market data aggregation from 50+ sources
- Model Deployment: Kubernetes orchestration for scalable inference
- Monitoring: Continuous model performance tracking and drift detection
- Retraining: Automated retraining pipelines with backtesting validation
Security Architecture
- Key Management: Hardware security modules (HSMs) for private key storage
- Multi-Sig: Gnosis Safe integration for institutional governance
- Rate Limiting: Transaction velocity controls to prevent drain attacks
- Monitoring: 24/7 anomaly detection on all contract interactions
- Insurance: Smart contract insurance coverage through Nexus Mutual
Integration Layer
- APIs: RESTful and GraphQL endpoints for programmatic access
- Webhooks: Real-time notifications for position updates and alerts
- SDKs: JavaScript/TypeScript, Python, and Go client libraries
- Documentation: Comprehensive API docs with interactive testing
- Support: Dedicated technical support for integration partners
Continuous Research & Development
Our R&D division focuses on developing new strategies, improving AI models, and advancing the state of quantitative methods in decentralized finance.
Strategy Research
Continuous exploration of new yield generation mechanisms including emerging DeFi primitives, novel derivative structures, and cross-protocol composability opportunities.
Model Enhancement
Ongoing improvement of AI models through expanded training datasets, architecture refinements, and integration of new market features and risk factors.
Stress Testing
Regular scenario analysis and stress testing across historical crises (March 2020, May 2021, FTX collapse) to validate risk parameters.
Academic Collaboration
Partnerships with university research groups studying DeFi mechanics, market microstructure, and risk management innovations.
Infrastructure Optimization
Continuous improvement of execution efficiency, gas optimization techniques, and cross-chain routing algorithms to reduce costs.
New Chain Integration
Evaluation and integration of emerging Layer 1s and Layer 2s that offer unique opportunities or improved execution economics.
What We Measure & How We Report
Transparency extends beyond risk metrics to include comprehensive performance reporting and attribution analysis for all strategies and portfolios.
Performance Metrics
- Total Return: Cumulative percentage return since inception
- Annualized Return: Geometric mean return expressed annually
- Sharpe Ratio: Risk-adjusted return (excess return / volatility)
- Maximum Drawdown: Largest peak-to-trough decline observed
- Recovery Time: Days required to recover from drawdowns
- Win Rate: Percentage of profitable days/weeks/months
- Profit Factor: Gross profits divided by gross losses
Risk Metrics
- Volatility: Standard deviation of returns (daily/monthly/annual)
- Value at Risk (VaR): 95th/99th percentile loss expectations
- Beta: Sensitivity to Bitcoin and Ethereum price movements
- Correlation: Correlation to major crypto assets and indices
- Downside Deviation: Volatility of negative returns only
- Sortino Ratio: Return / downside deviation (better than Sharpe)
- Calmar Ratio: Return / maximum drawdown ratio
Reporting Commitment
"We publish strategy performance data with the same rigor expected from traditional asset managers. All returns are net of fees, include transaction costs, and reflect actual executed trades—not backtested simulations. When strategies underperform, we report it transparently and explain why."
Experience AI-Powered Risk-Defined Yield
Our technology infrastructure is ready to serve your yield generation needs. Whether you're an individual investor or institutional allocator, apply for access today.