Investment thesis
Momentum & swing — economic intuition. Cross-sectional and time-series momentum are among the most documented anomalies in empirical asset pricing (Jegadeesh-Titman, Asness et al.). The thesis: investors under-react to gradual information and over-react late, leaving a multi-day window where recent winners continue. Squeeze and volatility-compression variants add a regime filter to reduce drawdowns in choppy markets.
Risk-adjusted performance — live track record
Forward-tested daily against live market data. Metrics derived from end-of-day portfolio marks; methodology documented on the Due Diligence and About pages.
| Return | Value | Risk-adjusted | Value | |
|---|---|---|---|---|
| Current portfolio worth | $10289.82 | Sharpe ratio | 5.46 | |
| Total return | 2.90% | Sortino ratio | 8.02 | |
| CAGR | 24.86% | Calmar ratio | 35.24 | |
| Volatility (annualised) | 5.30% | Profit factor | 2.78 | |
| Days live | 26 | Maximum drawdown | -0.71% |
Process consistency
| Positive months | 100.0% |
| Best month | 1.93% |
| Worst month | 0.77% |
| Recovery from max drawdown | 16 days |
Equity curve
Live track record — forward-tested performance from the strategy's production start date.
Drawdown profile
Underwater curve — percentage below the running high-water mark. Institutional allocators read this before the equity curve.
Current holdings
| Symbol | Quantity |
|---|---|
| IAU | 19.2791 |
| IJS | 14.1342 |
| USD | 4929.4585 |
| VTI | 4.9926 |
Research & documentation
- Strategy deep-dive: GoldenButterflyMomBot: strategy deep-dive & live performance
- Reference implementation:
tradingbot/goldenbutterflymombot.py - Framework: python_tradingbot_framework (open source, fully inspectable)
Related strategies
Other strategies in the Momentum & swing family:
- SqueezeMomentumBot · research note- SwingTitaniumBot · research note Or view the full strategy roster.
For professional investors
Request the investor deck, DDQ, and extended analytics. Firm-gated and reviewed manually.
Request access