Every moving average involves a fundamental tradeoff: shorter periods respond quickly to price changes but produce noisy, choppy signals; longer periods are smooth but lag significantly behind price. The Hull Moving Average was designed to break this tradeoff — Alan Hull's formula produces a line as smooth as a longer-period moving average but with the responsiveness of a much shorter one. This is achieved by calculating the difference between two WMAs (Weighted Moving Averages) and applying a final WMA to this difference — the mathematical equivalent of a moving average that "looks ahead" to estimate where the average will be, reducing the inherent retrospective lag. For automated crypto trading, the HMA's reduced lag means trend signals fire earlier in the trend, closer to the actual turning point rather than well after it. Earlier entry means better average entry prices and larger potential profit per trend move. DennTech implements HMA crossover, HMA slope, and HMA-ATR combined strategies. Compare editions at the pricing page.
Related strategies: EMA, Supertrend, TRIX.
Hull Moving Average Formula
HMA(N) = WMA(2 × WMA(N/2) - WMA(N), sqrt(N)) Step 1: Calculate WMA(N/2) — weighted moving average of half the period Step 2: Calculate WMA(N) — weighted moving average of full period Step 3: Raw = 2 × WMA(N/2) - WMA(N) (amplifies recent price signal) Step 4: HMA = WMA(Raw, sqrt(N)) (smoothing of the amplified signal) Example with N=16: HMA(16) = WMA(2 × WMA(8) - WMA(16), 4) Final period is sqrt(16) = 4 The doubling of WMA(N/2) minus WMA(N) creates a "extrapolation" of recent price momentum The final WMA(sqrt(N)) smooths the result to remove noise from the extrapolation
HMA vs EMA vs SMA — Lag Comparison
| Moving Average | Period 20 | Signal Lag | Noise Level |
|---|---|---|---|
| SMA(20) | Equal weight, 20 periods | Highest — full 10-period lag | Low (smoothest) |
| EMA(20) | Exponential decay weighting | Moderate — ~6-8 period lag | Moderate |
| HMA(20) | WMA-based formula | Lowest — ~2-4 period lag | Slightly higher than EMA |
HMA's reduced lag comes at a cost: slightly more noise/whipsaw than SMA or EMA at equivalent periods. The standard approach is to use a longer HMA period than you would with EMA to compensate: HMA(20) ≈ EMA(14) in responsiveness but HMA(20) is smoother than EMA(14). Start at the pricing page.
HMA Strategy Modes in DennTech
Mode 1: HMA Slope Direction
HMA slope turning upward (current HMA above previous HMA) = bullish trend signal. HMA slope turning downward = bearish. Single indicator trend direction filter. ATR stop required. See our ATR guide.
Mode 2: HMA Crossover
Short HMA (8 or 9 period) crosses above Long HMA (21 or 26 period) = bullish crossover. Standard dual-MA crossover logic with reduced lag vs EMA crossover. See our EMA crossover guide.
Mode 3: HMA Color Change
HMA bars colored green (above previous HMA value) or red (below) — enter long on first green bar after red; exit on first red after green. Same as slope direction but visualized as histogram colors for clarity.
Frequently Asked Questions
- Does the Hull Moving Average outperform EMA in crypto bot backtesting?
- The HMA's performance vs EMA in backtesting depends on the market regime. In strong trending markets (clear directional moves lasting weeks), HMA's reduced lag provides earlier entries and exits — resulting in better Profit Factor than equivalent EMA periods. In ranging/choppy markets, HMA's slightly higher noise generates more whipsaws than EMA at equivalent smoothness, resulting in lower Profit Factor. Overall, across multiple market regimes in a long backtest (3+ years), the difference between well-configured HMA and EMA strategies is often modest — both capture the same fundamental trend moves. The HMA's real advantage manifests most clearly at trend turning points (bear-to-bull and bull-to-bear transitions) where its earlier signal means a better entry or earlier exit. ADX filtering significantly improves HMA performance by suppressing signals during the ranging periods where HMA is weaker. See our ADX guide. Compare editions at the pricing page.
- What HMA period should I use for Bitcoin Daily chart automated trading?
- For BTC Daily chart HMA trend following, common effective period ranges are HMA(16) through HMA(26). HMA(20) or HMA(21) is the most commonly used starting point — it approximates an EMA(14) in lag but with smoother visualization. At HMA(20) on BTC Daily: approximately 15–25 trend direction changes per year (slightly more than EMA(21) due to reduced lag). For a less frequent, higher-conviction signal set, HMA(26) or even HMA(34) reduces signals to 10–18 per year with wider stop distances. For 4H chart HMA where you want responsiveness for shorter-duration position trades: HMA(9) or HMA(12) provides appropriate frequency. Always backtest your chosen period on at least 3 years of BTC data. Explore the live demo. Start at the pricing page.
- Can HMA replace EMA in all DennTech strategies or are some strategies specifically designed for EMA?
- Most DennTech trend-following strategies that use EMA can substitute HMA for potentially improved lag characteristics — the entry/exit logic is identical (crossover, slope change, price vs MA relationship). DennTech's strategy builder allows substituting the MA type (SMA, EMA, WMA, HMA) in strategies that take a moving average as input. Strategies where HMA substitution makes sense: EMA crossover → HMA crossover (earlier signals), EMA trend filter → HMA trend filter (less lag in trend detection). Strategies where EMA is specifically designed-in and HMA substitution is less appropriate: MACD (which uses EMA by mathematical definition — changing to HMA creates a different indicator entirely); Ichimoku (which uses SMA-based calculations as part of its complete system). For dedicated trend-following and trend-filter uses, HMA substitution for EMA is generally worth testing. Start at the pricing page.
One additional practical advantage of HMA for trend-following is its visual clarity. Because the HMA responds more quickly to price direction changes, its slope (rising vs falling) clearly reflects the current trend direction at each moment rather than lagging by several periods as SMA does. Traders monitoring a strategy in real-time find HMA easier to read than SMA precisely because it more closely mirrors what price is actually doing right now rather than what it was doing 10 periods ago. For automated strategy monitoring and debugging — checking whether the bot is correctly identifying the trend — HMA's responsiveness makes it easier to manually verify that the bot's trend detection is aligned with visible price action. DennTech's strategy logs display the current HMA value on each candle, making verification straightforward. Full configuration and examples at DennTech docs. Compare editions at the pricing page.
Moving averages: HMA (this guide), EMA, TRIX. All at the strategies page.