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60 lines
2.9 KiB
Markdown
60 lines
2.9 KiB
Markdown
# DWMA: Double Weighted Moving Average
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> "If one WMA is good, two must be better. DWMA is for when you want your signal so smooth it looks like it's been sanded, polished, and waxed."
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DWMA (Double Weighted Moving Average) is exactly what it says on the tin: a Weighted Moving Average of a Weighted Moving Average. Unlike DEMA, which tries to *remove* lag, DWMA accepts lag as the price of admission for superior noise reduction. It produces a curve that is incredibly smooth, ideal for identifying long-term trends without getting faked out by market chop.
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## Historical Context
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There is no single "inventor" of DWMA; it's a natural extension of linear filtering. It represents a higher-order filter that prioritizes recent data (via WMA) but applies a second pass to iron out any remaining wrinkles. It's the heavy artillery of smoothing.
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## Architecture & Physics
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DWMA applies a linear weight kernel (triangle window) twice.
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1. **Pass 1**: Calculate WMA of the price.
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2. **Pass 2**: Calculate WMA of the result from Pass 1.
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The effective window size is roughly $2 \times \text{Period}$, and the lag is cumulative. This is not for high-frequency scalping; this is for determining if the market is actually bullish or just having a manic episode.
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## Mathematical Foundation
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$$ \text{WMA}_1 = \text{WMA}(P, N) $$
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$$ \text{DWMA} = \text{WMA}(\text{WMA}_1, N) $$
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The weight profile of a single WMA is triangular. The weight profile of a DWMA approaches a Gaussian-like shape (central limit theorem in action), but heavily skewed towards recent data due to the WMA's linear weighting.
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## Performance Profile
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Despite the double pass, it remains O(1) thanks to the optimized WMA implementation.
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| Metric | Score | Notes |
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| :--- | :--- | :--- |
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| **Throughput** | ★★★★☆ | 2x cost of WMA (still O(1)). |
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| **Allocations** | ★★★★★ | 0 bytes; hot path is allocation-free. |
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| **Complexity** | ★★★★★ | O(1) constant time update. |
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| **Precision** | ★★★★★ | `double` precision. |
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### Zero-Allocation Design
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DWMA is implemented by chaining two `Wma` instances. Since `Wma` is zero-allocation, DWMA inherits this property.
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## Validation
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Validated against chained WMA implementations in standard libraries.
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| Library | Status | Notes |
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| :--- | :--- | :--- |
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| **QuanTAlib** | ✅ | Validated against `WMA(WMA)`. |
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| **Skender** | ✅ | Validated against chained `GetWma`. |
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| **TA-Lib** | ✅ | Validated against chained `TA_WMA`. |
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| **Tulip** | ✅ | Validated against chained `wma`. |
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| **Ooples** | ✅ | Validated against chained `CalculateWeightedMovingAverage`. |
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### Common Pitfalls
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1. **Lag**: This indicator lags. A lot. Do not use it for entry signals on tight timeframes. Use it for trend filtering (e.g., "only buy if price > DWMA").
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2. **Warmup**: It takes roughly $2 \times N$ bars to produce valid data.
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3. **Confusion with DEMA**: DEMA = Fast, DWMA = Smooth. Do not mix them up.
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