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
|
Elastic Net with Inverse-Variance Weights
#68
|
|---|---|---|
| Primary Rankings | ||
| Sharpe Ratio Sharpe Ratio Risk-adjusted return: annualized return divided by annualized volatility. | 2.5212 (best) | 0.7593 |
| Rank Rank Position on the leaderboard, ordered by Sharpe ratio. | #34 | #68 |
| Returns | ||
| Annualized Return Annualized Return Average yearly return, after scaling the portfolio to the 10% volatility target. | 25.21% (best) | 7.59% |
| Risk | ||
| Max Drawdown Max Drawdown Largest peak-to-trough decline during the test period. | -16.63% (best) | -28.66% |
| Downside Deviation Downside Deviation Standard deviation of negative monthly returns only. | 1.450% (best) | 1.958% |
| Annualized Downside Dev Annualized Downside Deviation Downside deviation in annual terms. | 5.02% (best) | 6.78% |
| Risk-Adjusted Performance | ||
| Sortino Ratio Sortino Ratio Return per unit of downside risk: like Sharpe, but only negative volatility counts. | 5.0195 (best) | 1.1195 |
| Calmar Ratio Calmar Ratio Annualized return divided by the maximum drawdown. | 1.5157 (best) | 0.2649 |
| Win Rate Win Rate Share of months with a positive return. | 77.0% (best) | 64.0% |
| Distribution | ||
| Skewness Skewness Asymmetry of returns. Positive skew means more large gains than large losses. | 0.136 | 1.066 |
| Kurtosis Kurtosis Tail thickness. Higher values mean more extreme months, in either direction. | 0.530 | 12.680 |
| Volatility Targeting | ||
| Raw Volatility Raw Volatility Volatility of the portfolio before it was scaled to the 10% target. | 14.65% | 18.93% |
| Scaling Factor Scaling Factor Multiplier applied to the portfolio to reach the 10% volatility target. | 0.683 | 0.528 |
| 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 | 0.90 |
| Alpha (ann.) Alpha (ann.) Average yearly return not explained by market exposure (the monthly regression alpha × 12). | 25.03% (best) | 3.58% |
| Information Ratio Information Ratio Annualized alpha per unit of residual risk: alpha ÷ std(residuals) × √12. | 2.5016 (best) | 0.5301 |
| R² R² Share of the return variance explained by market movements. | 0.1% | 54.6% |
| Alpha t-stat Alpha t-stat Statistical significance of the alpha estimate. A |t| above about 2 suggests it is not chance. | 14.41 | 3.05 |
| Metadata | ||
| Language | R | Python |
| Competition Year | 2024 | 2024 |
| Entry Type | Benchmark | User |