@petegaskell

For sentiment-based signals, statistical validation is essential. Permutation tests and bootstrap resampling help confirm whether observed correlations are genuine or spurious. By shuffling data labels or resampling with replacement, analysts can generate null distributions to benchmark actual signal strength. If the sentiment signal significantly outperforms these randomized baselines, it suggests robustness. Otherwise, the effect may be noise. This approach guards against overfitting and ensures confidence in deploying sentiment signals within trading systems. Without such statistical checks, investors risk relying on fragile or coincidental relationships that fail in live markets.

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