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The key AI strategy traps: overfitting, data leakage and regime change

Part II explains why rapidly generating features and strategies can increase the risk of fitting history. Data availability timing, knowledge embedded in a model and out-of-sample robustness require particular control.

Author: Prime ASI ResearchUpdated: 26 July 2026

Source facts and context

Part II explains why rapidly generating features and strategies can increase the risk of fitting history. Data availability timing, knowledge embedded in a model and out-of-sample robustness require particular control.

PRIME ASI analysis

Assessing Algo Trade AI requires train-test separation, experiment logging and validation after transaction costs. An attractive backtest curve alone is not evidence of scalability.

Barriers, risks and limitations

This is educational content. It does not disclose Algo Trade AI parameters or performance.

Primary source

Two Sigma

AI in Investment Management: 2026 Outlook, Part II

Open source material

This material is educational and informational. It does not constitute an investment recommendation, an offer or any assurance regarding the future performance of Prime ASI S.A. or its portfolio companies.

The key AI strategy traps: overfitting, data leakage and regime change | PRIME ASI