Dynamically Regularized MVP

Performance Ranking

0.15 13.9th percentile (Sharpe Ratio) 4.39

Better than 13.9% of the 79 other models

Performance Metrics

Primary Rankings

Sharpe Ratio Sharpe Ratio Risk-adjusted return: annualized return divided by annualized volatility. 0.7296

Rank Rank Position on the leaderboard, ordered by Sharpe ratio. #69

Returns

Annualized Return Annualized Return Average yearly return, after scaling the portfolio to the 10% volatility target. This model: Better than 14% of the 79 other models. 7.30%

Best 12M Return Best 12M Return The best compounded return over any 12 consecutive months of the test period. This model: Better than 3% of the 79 other models. 41.28% Aug 1996 – Jul 1997

Worst 12M Return Worst 12M Return The worst compounded return over any 12 consecutive months of the test period. This model: Better than 13% of the 79 other models. -26.79% Mar 1999 – Feb 2000

Risk

Max Drawdown Max Drawdown Largest peak-to-trough decline during the test period. This model: Better than 1% of the 79 other models. -38.72%

Downside Deviation Downside Deviation Standard deviation of negative monthly returns only. This model: Better than 3% of the 79 other models. 2.387%

Annualized Downside Dev Annualized Downside Deviation Downside deviation in annual terms. This model: Better than 3% of the 79 other models. 8.27%

Risk-Adjusted Performance

Sortino Ratio Sortino Ratio Return per unit of downside risk: like Sharpe, but only negative volatility counts. This model: Better than 10% of the 79 other models. 0.8825

Calmar Ratio Calmar Ratio Annualized return divided by the maximum drawdown. This model: Better than 9% of the 79 other models. 0.1884

Win Rate Win Rate Share of months with a positive return. This model: Better than 18% of the 79 other models. 63.7%

Distribution

Skewness Skewness Asymmetry of returns. Positive skew means more large gains than large losses. -0.894 (Left skew (risky))

Kurtosis Kurtosis Tail thickness. Higher values mean more extreme months, in either direction. 2.978 (Near-normal)

Volatility Targeting

Raw Volatility Raw Volatility Volatility of the portfolio before it was scaled to the 10% target. 1.75%

Scaling Factor Scaling Factor Multiplier applied to the portfolio to reach the 10% volatility target. 5.718

Observations Observations Number of monthly returns used for the evaluation. 408 months

Market Exposure (CAPM)

Beta Beta Sensitivity to market movements. 1.0 moves one-for-one with the market. 0.07

Alpha (ann.) Alpha (ann.) Average yearly return not explained by market exposure (the monthly regression alpha × 12). This model: Better than 11% of the 79 other models. 4.01%

Information Ratio Information Ratio Annualized alpha per unit of residual risk: alpha ÷ std(residuals) × √12. This model: Better than 13% of the 79 other models. 0.5027

R² R² Share of the return variance explained by market movements. 36.6%

Alpha t-stat Alpha t-stat Statistical significance of the alpha estimate. A |t| above about 2 suggests it is not chance. 2.90

Benchmark Comparison

vs. Benchmarks

Dynamically Regularized MVP

0.7296

Benchmark: Markowitz-ML

2.5212

Benchmark: Instrumented PCA factor portfolio

1.9481

Benchmark: Kozak-Nagel-Santosh rank-weighted factors portfolio

1.4195

Benchmark: Minimum Variance

0.9470

Benchmark: Factor-ML

0.8901

Benchmark: Equal-weight portfolio

0.4912

Performance Radar

Each axis shows the model's percentile rank within the leaderboard (outer edge = best). Customize the metrics using the dropdowns below.

vs. Leaderboard

Metric	This Model	Average	Top Model	vs. Avg
Sharpe Ratio Sharpe Ratio Risk-adjusted return: annualized return divided by annualized volatility.	0.7296	2.2380	4.3949	-67.4% (worse)
Sortino Ratio Sortino Ratio Return per unit of downside risk: like Sharpe, but only negative volatility counts.	0.8825	4.7888	17.3078	-81.6% (worse)
Calmar Ratio Calmar Ratio Annualized return divided by the maximum drawdown.	0.1884	2.0343	11.7867	-90.7% (worse)
Information Ratio Information Ratio Annualized alpha per unit of residual risk: alpha ÷ std(residuals) × √12.	0.5027	2.2041	4.3562	-77.2% (worse)
Win Rate Win Rate Share of months with a positive return.	63.7%	75.4%	91.2%	-15.5% (worse)
Annualized Return Annualized Return Average yearly return, after scaling the portfolio to the 10% volatility target.	7.30%	22.38%	43.95%	-67.4% (worse)
Max Drawdown Max Drawdown Largest peak-to-trough decline during the test period.	-38.72%	-18.80%	-3.51%	-106.0% (worse)

Model Details

Language Python

Competition Year 2024

First Submitted Jan 31, 2026

Scored Jan 31, 2026

Downloads

Download Code (Python) 33 downloads Download Documentation 27 downloads

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