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# Covariance: Covariance
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Statistic |
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| **Inputs** | Source (close) |
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| **Parameters** | `period`, `isPopulation` (default false) |
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| **Outputs** | Single series (Cov) |
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| **Output range** | Varies (see docs) |
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| **Warmup** | `period` bars |
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### TL;DR
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- Covariance measures the joint variability of two random variables.
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- Parameterized by `period`, `ispopulation` (default false).
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- Output range: Varies (see docs).
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- Requires `period` bars of warmup before first valid output (IsHot = true).
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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> "Correlation is just covariance normalized by standard deviation. But sometimes you want the raw, unadulterated relationship."
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Covariance measures the joint variability of two random variables. It indicates the direction of the linear relationship between variables.
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