Investment thesis
Portfolio optimisation — economic intuition. Given a universe of imperfectly-correlated return streams, convex optimisation (Markowitz, risk-parity, recursive decay) produces weights that dominate naive equal-weight on a risk-adjusted basis. The edge is not in alpha discovery but in the disciplined combination of existing signals — consistent with institutional multi-manager allocation.
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 | $10128.53 | Sharpe ratio | 0.34 | |
| Total return | 1.29% | Sortino ratio | 0.50 | |
| CAGR | 2.29% | Calmar ratio | 0.34 | |
| Volatility (annualised) | 7.71% | Profit factor | 1.08 | |
| Days live | 139 | Maximum drawdown | -6.76% |
Process consistency
| Positive months | 71.4% |
| Best month | 4.24% |
| Worst month | -5.33% |
| Recovery from max drawdown | 27 days |
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) | 0.51 | 0.00 | 0.38 |
| Bitcoin (BTC-USD) | 0.24 | 0.19 | 0.06 |
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 |
|---|---|
| 2B76.DE | 6.5355 |
| AMD | 0.4323 |
| BTEC.L | 38.1712 |
| DBMF | 27.9082 |
| GOOG | 0.2631 |
| IWDA.AS | 4.2583 |
| KDP | 5.7365 |
| L0CK.DE | 8.2767 |
| LLY | 0.1213 |
| META | 0.2732 |
| NTSX | 7.6706 |
| PGR | 1.6298 |
| QQQ | 0.5239 |
| SHV | 18.3598 |
| SQQQ | 11.7100 |
| TEAM | 0.0000 |
| UNH | 0.6366 |
| UPRO | 1.0874 |
| USD | 0.0000 |
| UUP | 71.2639 |
| VFH | 4.6271 |
| VLUE | 1.9607 |
| W1TA.DE | 1.4250 |
| XAIX.DE | 0.6636 |
Research & documentation
- Strategy deep-dive: SharpePortfolioOptWeeklyBot: strategy deep-dive & live performance
- Reference implementation:
tradingbot/sharpeportfoliooptweekly.py - Framework: python_tradingbot_framework (open source, fully inspectable)
Related strategies
Other strategies in the Portfolio optimisation family:
- RecursiveDecayHarvestBot · research note- SynthesizedHyperConvexityBot · 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