Comparing 2 models side-by-side
Each axis shows a model's percentile rank within the leaderboard (outer edge = best). Customize the metrics using the dropdowns below.
| Metric |
Nonlinear IPCA with Precision Weighting
#7
|
Benchmark: Instrumented PCA factor portfolio
#21
|
|---|---|---|
| Primary Rankings | ||
| Sharpe Ratio Sharpe Ratio Risk-adjusted return: annualized return divided by annualized volatility. | 3.3057 (best) | 1.9481 |
| Rank Rank Position on the leaderboard, ordered by Sharpe ratio. | #7 | #21 |
| Returns | ||
| Annualized Return Annualized Return Average yearly return, after scaling the portfolio to the 10% volatility target. | 33.06% (best) | 19.48% |
| Risk | ||
| Max Drawdown Max Drawdown Largest peak-to-trough decline during the test period. | -11.96% | -9.92% (best) |
| Downside Deviation Downside Deviation Standard deviation of negative monthly returns only. | 1.552% | 1.198% (best) |
| Annualized Downside Dev Annualized Downside Deviation Downside deviation in annual terms. | 5.38% | 4.15% (best) |
| Risk-Adjusted Performance | ||
| Sortino Ratio Sortino Ratio Return per unit of downside risk: like Sharpe, but only negative volatility counts. | 6.1498 (best) | 4.6958 |
| Calmar Ratio Calmar Ratio Annualized return divided by the maximum drawdown. | 2.7650 (best) | 1.9643 |
| Win Rate Win Rate Share of months with a positive return. | 85.0% (best) | 74.3% |
| Distribution | ||
| Skewness Skewness Asymmetry of returns. Positive skew means more large gains than large losses. | 0.408 | 1.387 |
| Kurtosis Kurtosis Tail thickness. Higher values mean more extreme months, in either direction. | 1.310 | 2.979 |
| Volatility Targeting | ||
| Raw Volatility Raw Volatility Volatility of the portfolio before it was scaled to the 10% target. | 2.36% | 374.37% |
| Scaling Factor Scaling Factor Multiplier applied to the portfolio to reach the 10% volatility target. | 4.243 | 0.027 |
| Observations Observations Number of monthly returns used for the evaluation. | 408 mo | 408 mo |
| Market Exposure (CAPM) | ||
| Beta Beta Sensitivity to market movements. 1.0 moves one-for-one with the market. | 0.02 | 2.99 |
| Alpha (ann.) Alpha (ann.) Average yearly return not explained by market exposure (the monthly regression alpha × 12). | 32.37% (best) | 18.81% |
| Information Ratio Information Ratio Annualized alpha per unit of residual risk: alpha ÷ std(residuals) × √12. | 3.2592 (best) | 1.8930 |
| R² R² Share of the return variance explained by market movements. | 1.6% | 1.5% |
| Alpha t-stat Alpha t-stat Statistical significance of the alpha estimate. A |t| above about 2 suggests it is not chance. | 18.77 | 10.90 |
| Metadata | ||
| Language | Python | Python |
| Competition Year | 2024 | 2024 |
| Entry Type | User | Benchmark |