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 |
Benchmark: Markowitz-ML
#34
|
Ridge-XGBoost Barra Long-Short
#39
|
|---|---|---|
| Primary Rankings | ||
| Sharpe Ratio Sharpe Ratio Risk-adjusted return: annualized return divided by annualized volatility. | 2.5212 (best) | 2.3745 |
| Rank Rank Position on the leaderboard, ordered by Sharpe ratio. | #34 | #39 |
| Returns | ||
| Annualized Return Annualized Return Average yearly return, after scaling the portfolio to the 10% volatility target. | 25.21% (best) | 23.74% |
| Risk | ||
| Max Drawdown Max Drawdown Largest peak-to-trough decline during the test period. | -16.63% (best) | -20.02% |
| Downside Deviation Downside Deviation Standard deviation of negative monthly returns only. | 1.450% | 1.446% (best) |
| Annualized Downside Dev Annualized Downside Deviation Downside deviation in annual terms. | 5.02% | 5.01% (best) |
| Risk-Adjusted Performance | ||
| Sortino Ratio Sortino Ratio Return per unit of downside risk: like Sharpe, but only negative volatility counts. | 5.0195 (best) | 4.7405 |
| Calmar Ratio Calmar Ratio Annualized return divided by the maximum drawdown. | 1.5157 (best) | 1.1861 |
| Win Rate Win Rate Share of months with a positive return. | 77.0% | 77.2% (best) |
| Distribution | ||
| Skewness Skewness Asymmetry of returns. Positive skew means more large gains than large losses. | 0.136 | 0.103 |
| Kurtosis Kurtosis Tail thickness. Higher values mean more extreme months, in either direction. | 0.530 | 0.262 |
| Volatility Targeting | ||
| Raw Volatility Raw Volatility Volatility of the portfolio before it was scaled to the 10% target. | 14.65% | 4.23% |
| Scaling Factor Scaling Factor Multiplier applied to the portfolio to reach the 10% volatility target. | 0.683 | 2.362 |
| 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. | 0.03 | -0.03 |
| Alpha (ann.) Alpha (ann.) Average yearly return not explained by market exposure (the monthly regression alpha × 12). | 25.03% (best) | 24.38% |
| Information Ratio Information Ratio Annualized alpha per unit of residual risk: alpha ÷ std(residuals) × √12. | 2.5016 (best) | 2.4522 |
| R² R² Share of the return variance explained by market movements. | 0.1% | 1.4% |
| Alpha t-stat Alpha t-stat Statistical significance of the alpha estimate. A |t| above about 2 suggests it is not chance. | 14.41 | 14.13 |
| Metadata | ||
| Language | R | Python |
| Competition Year | 2024 | 2024 |
| Entry Type | Benchmark | User |