Synthetic Dividend Strategy

Research on Volatility Harvesting

This project investigates systematic approaches to volatility harvesting through algorithmic rebalancing strategies. The Synthetic Dividend algorithm maintains constant portfolio value through symmetric rebalancing, potentially generating cash flows from market oscillations while preserving initial positions.

The research examines whether volatility itself can be systematically harvested through disciplined rebalancing, independent of directional market predictions.

Core Mechanism:
Buy at: P / (1 + r) | Sell at: P × (1 + r)
Where r = rebalance trigger (e.g., 9.05% for sd8)

263

Tests Passing

33%

Code Coverage

9.05%

Default Rebalance Trigger

317

Lines of Publication-Quality Code

🎯 Core Algorithm

Symmetric LIFO rebalancing (when STCG == LTCG)
Multi-bracket gap handling
Profit sharing mechanism
ATH-only mode option
Volatility alpha calculation

📊 Research & Theory

Volatility Alpha thesis
Asset class comparisons
Optimal rebalancing analysis
Gap bonus assessment
Academic-grade documentation

🏗️ Architecture

Clean transaction-based model
Portfolio & Account separation
Debt/margin support
Extensible algorithm framework
Comprehensive backtesting engine

📈 Analysis Tools

Batch comparison framework
Visualization tools
Statistical validation
Performance metrics
Coverage reporting

🧪 Testing

263 comprehensive tests
Property-based testing
Symmetry verification
Multi-scenario coverage
Continuous integration ready

📝 Documentation

Theory documents
Research plans
Coding philosophy
Migration guides
Naming conventions