All statistics are computed from daily return series and annualized using a 366-day year. Returns are net of fees.
| Metric | Coinchange USDC Equilibrium |
|---|---|
| Cumulative Return | 42.08% |
| Annualized Return | 19.23% |
| Annualized Volatility | 6.90% |
| Sharpe Ratio | 2.58 |
| Sortino Ratio | 4.68 |
| Calmar Ratio | 4.61 |
| Max Drawdown | -4.57% |
| % Positive Days | 49.4% |
| Best Day | 2.40% |
| Worst Day | -2.21% |
| Skewness | 1.49 |
| Excess Kurtosis | 10.17 |
| VaR (95%) | -0.37% |
| CVaR (95%) | -0.61% |
Portfolio NAV (left axis) is plotted against the Bitcoin spot price (right axis) to illustrate how the portfolio’s value evolves relative to the underlying asset. Because the strategy employs hedging and multi-sleeve construction, the portfolio line is expected to exhibit meaningfully lower volatility than Bitcoin itself while still participating in directional upside over time.
Volatility Bands plot the cumulative NAV against a 20-day moving average with bands at ±2 standard deviations. The width of the shaded band reflects the portfolio’s recent volatility — wider bands indicate periods of elevated risk, while narrower bands signal more stable performance.
Rolling 30-day annualized volatility tracks how the standard deviation of daily returns evolves over time. The portfolio (left axis) is shown alongside Bitcoin spot (right axis) to highlight how effectively the strategy dampens raw Bitcoin volatility.
The drawdown chart shows, at each point in time, the percentage decline from the most recent cumulative NAV peak. Deeper troughs represent larger capital-at-risk periods, and the shape of each trough reveals how quickly the portfolio recovered.
Return distributions display histograms of daily returns (in percentage terms) overlaid with a normal (Gaussian) fit. Deviations from the normal curve—such as fat tails or skew—highlight non-normal risk that standard metrics like volatility may understate.
Correlation matrices show the pairwise linear correlation between sleeve-level daily returns. Values near +1 indicate sleeves that move together, while values near –1 indicate diversifying offsets. Lower inter-sleeve correlation generally implies a more robust portfolio construction.
Monthly return attribution breaks down each month’s portfolio return into the contributions from individual sleeves. This reveals which strategies are driving performance in any given period and helps assess whether returns are concentrated in a single sleeve or well-distributed across the portfolio.