160 minutes
Learn to build robust, comprehensive backtesting frameworks specifically designed for MEV strategies. Master modular architecture, realistic market simulation, and performance analysis.
Key Topics:
- Core backtesting architecture and components
- Strategy base classes and implementations
- Realistic market data generation
- Transaction-level simulation with gas modeling
- Performance metrics and statistical analysis
140 minutes
Master comprehensive data collection, cleaning, and preprocessing pipelines necessary for robust backtesting and live trading. Work with blockchain data, DEX information, and market microstructure.
Key Topics:
- Web3 and API-based blockchain data extraction
- Real-time data streaming and collection
- Database design and data storage management
- Data quality validation and cleaning
- Feature engineering for MEV strategies
180 minutes
Build sophisticated transaction simulators that account for network congestion, execution failures, and competitive dynamics. Learn realistic transaction execution modeling and mempool-aware simulation.
Key Topics:
- Realistic transaction execution models
- Gas price dynamics and network congestion
- AMM price impact modeling
- Mempool simulation and front-running
- Batch transaction processing
170 minutes
Master sophisticated price impact models, liquidity dynamics, and order flow analysis. Learn to model market microstructure effects in decentralized finance markets.
Key Topics:
- Advanced price impact models
- Liquidity dynamics and depth analysis
- Order flow and market microstructure effects
- Adaptive models for changing conditions
- Cross-asset and cross-chain scenarios
190 minutes
Develop frameworks for understanding MEV strategy performance under extreme market conditions. Learn Monte Carlo simulations, stress testing, and extreme event modeling.
Key Topics:
- Monte Carlo simulation frameworks
- Market crash and volatility scenarios
- Extreme Value Theory and tail risk
- Adaptive scenario generation
- Systemic risk and correlation breakdowns
160 minutes
Implement comprehensive performance metrics, statistical validation techniques, and continuous monitoring frameworks. Learn out-of-sample testing and performance attribution.
Key Topics:
- Comprehensive performance metrics
- Statistical significance testing
- Out-of-sample validation frameworks
- Performance attribution analysis
- Real-time monitoring and alerts