Henderson Weighted Moving Average
period = 14 (5–200) Overview
The Henderson Weighted Moving Average (HWMA) is a sophisticated smoothing technique that applies symmetric weights to price data, with the highest weight at the center and weights tapering off towards the edges. Originally developed by Robert Henderson in 1916 for actuarial graduation, this moving average has proven exceptionally effective for financial time series analysis due to its ability to handle substantial randomness while preserving trend information.
What sets HWMA apart is its ability to reproduce polynomials up to degree 3, allowing it to capture trend turning points more accurately than simpler moving averages. The symmetric nature of the weights means it doesn't introduce phase shift, while the polynomial-based weighting minimizes the sum of squared third differences, resulting in exceptionally smooth output that still responds to genuine price movements.
Interpretation & Trading Signals
Trend Identification:
- Rising HWMA: Upward trend confirmed with reduced noise interference
- Falling HWMA: Downward trend with smooth directional confirmation
- HWMA Slope: Steeper slopes indicate stronger, more reliable trends
- Turning Points: Excellent at capturing trend reversals due to polynomial properties
Trading Applications:
- Trend Filter: Price above HWMA = bullish bias, below = bearish bias
- Support/Resistance: Acts as dynamic support in uptrends, resistance in downtrends
- Noise Reduction: Superior smoothing for high-frequency or volatile data
- Crossover Signals: Price crossing HWMA indicates potential trend change
Key Characteristics:
- Symmetric Weights: No phase shift, centered on current price
- Polynomial Reproduction: Can accurately follow cubic trends
- Period Requirements: Must use odd number >= 5 for proper calculation
- Best Use: Ideal for noisy markets needing smooth trend extraction
Example Usage
Code examples will be available once the Rust implementation is complete.
Performance Analysis
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