Investment thesis
Tree-based ML — economic intuition. Supervised non-linear models exploit conditional relationships between engineered features (volatility regime, cross-asset spreads, calendar effects) and short-horizon return distributions. The edge comes from noisy but persistent micro-structure in FX and metals where linear factor models under-fit interaction terms.
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 | $10009.49 | Sharpe ratio | 0.21 | |
| Total return | 0.09% | Sortino ratio | 0.14 | |
| CAGR | 0.23% | Calmar ratio | 0.23 | |
| Volatility (annualised) | 1.44% | Profit factor | 1.08 | |
| Days live | 82 | Maximum drawdown | -0.98% |
Process consistency
| Positive months | 20.0% |
| Best month | 0.09% |
| Worst month | 0.00% |
| Recovery from max drawdown | still underwater |
Market independence
Correlation and beta versus passive benchmarks, computed over the full live series.
| Benchmark | Correlation | 90-day rolling correlation | Beta |
|---|---|---|---|
| S&P 500 (SPY) | 0.16 | 0.00 | 0.03 |
| Bitcoin (BTC-USD) | 0.12 | 0.00 | 0.01 |
A correlation materially below 1.0 to both benchmarks indicates the strategy’s returns are not a simple re-expression of long equity or long crypto beta.
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 |
|---|---|
| EURUSD=X | 8490.0501 |
| USD | 0.0000 |
Research & documentation
- Strategy deep-dive: EURUSDTreeBot: strategy deep-dive & live performance
- Reference implementation:
tradingbot/eurusdtreebot.py - Framework: python_tradingbot_framework (open source, fully inspectable)
Related strategies
Other strategies in the Tree-based ML family:
- XAUSyntheticMetalTreeBot · research note- XAUZenbotTreeBot · research note Or view the full strategy roster.
For professional investors
Request the investor deck, DDQ, and extended analytics. Firm-gated and reviewed manually.
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