Q1 2026 Competition Results: Lessons from the Top Performers
Q1 2026 Competition Results: Lessons from the Top Performers
The Q1 2026 Momentum Challenge has concluded, and the results are in. Congratulations to all 247 participants!
Final Standings
| Rank | Participant | Sharpe | Max DD | Calmar |
|---|---|---|---|---|
| 1 | EnsembleKing | 2.14 | -8.3% | 3.09 |
| 2 | QuantDev42 | 1.98 | -6.1% | 2.87 |
| 3 | MicroAlpha | 1.87 | -11.2% | 1.94 |
| 4 | DataSciPro | 1.82 | -9.7% | 2.21 |
| 5 | RiskQuant | 1.76 | -5.2% | 3.42 |
Common Patterns Among Top Performers
1. Feature Engineering > Model Complexity
The top 10 strategies all used relatively simple models (Ridge regression, gradient boosting) with carefully engineered features. None of the top performers used deep learning as their primary model.
2. Risk Management Was Key
Strategies with lower max drawdown tended to rank higher, even if their raw Sharpe was slightly lower. The top 5 all had max drawdowns under 12%.
3. Turnover Control
High-turnover strategies suffered from transaction cost penalties. The median turnover of top-10 strategies was 15% daily, compared to 45% for the median participant.
What We Learned
The quant community continues to prove that discipline beats complexity. Simple, well-validated strategies with strong risk management consistently outperform overfit models.
Stay tuned for the Q2 challenge announcement next week!