Q2 2026 competition early discussion

Thanks for sharing! This is exactly the kind of insight that helps the community grow. Bookmarking this thread.

I've found that sector neutrality is a key factor in the scoring. Strategies that are long one sector and short another tend to underperform.

The documentation for the API is at /docs -- it's OpenAPI/Swagger format. Very helpful for understanding submission formats.

I've found that sector neutrality is a key factor in the scoring. Strategies that are long one sector and short another tend to underperform.

The documentation for the API is at /docs -- it's OpenAPI/Swagger format. Very helpful for understanding submission formats.

Great analysis! I've been using a similar approach with rolling z-scores and it's been working well for mean reversion signals.

For factor models, I'd strongly recommend the Fama-French 5-factor model as a starting point. It captures most systematic risk.

Has anyone tried using attention mechanisms for this? The temporal attention weights could tell you which historical periods are most relevant.

Good point about overfitting. My rule of thumb: never trust a backtest with fewer than 500 observations in the out-of-sample period.