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# RMA: Running Moving Average
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Trend (IIR MA) |
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| **Inputs** | Source (close) |
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| **Parameters** | `period` |
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| **Outputs** | Single series (Rma) |
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| **Output range** | Tracks input |
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| **Warmup** | `ema.WarmupPeriod` bars |
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### TL;DR
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- The Running Moving Average (RMA), also known as the Smoothed Moving Average (SMMA) or Wilder's Moving Average, is the backbone of J.
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- Parameterized by `period`.
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- Output range: Tracks input.
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- Requires `ema.WarmupPeriod` 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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> "Wilder didn't like standard EMA weighting. He wanted history to decay slower. So he invented RMA, which is just EMA with a different alpha, confusing traders for 40 years."
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The Running Moving Average (RMA), also known as the Smoothed Moving Average (SMMA) or Wilder's Moving Average, is the backbone of J. Welles Wilder's most famous indicators: RSI, ATR, and ADX. It is functionally identical to an Exponential Moving Average (EMA), but with a smoothing factor ($\alpha$) of $1/N$ instead of $2/(N+1)$. This results in a longer "memory" and slower decay than a standard EMA of the same period.
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@@ -94,4 +111,4 @@ Validated against Skender and Ooples.
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1. **Initialization**: Like EMA, RMA requires a "warmup" period to converge. Wilder often initialized with a Simple Moving Average (SMA) of the first $N$ bars. QuanTAlib follows this convention.
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2. **Naming**: Often called SMMA (Smoothed Moving Average) in other libraries.
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3. **Period Mismatch**: Using an EMA(14) where an RMA(14) is expected will result in a much faster-moving line (equivalent to RMA(7.5)).
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3. **Period Mismatch**: Using an EMA(14) where an RMA(14) is expected will result in a much faster-moving line (equivalent to RMA(7.5)).
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