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AI stock models can suffer from overfitting or underestimated, which compromises their accuracy and generalizability. Here are ten methods to assess and reduce the risks associated with an AI stock forecasting model 1. Examine model performance on In-Sample Vs. Out of-Sample data Reason: High precision in samples, but low performance from the samples indicates that the system is overfitting. Poor performance on both could be a sign of underfitting. What should you do: Examine whether your model is performing consistently when using the in-sample and out-of-sample data. Performance that is lower than expected indicates the possibility of an overfitting. 2. …