Hull Moving Average (HMA) is a fast and smooth moving average that reduces lag and helps traders identify trend direction with improved accuracy
Hull Moving Average (HMA) Explained: What It Is and Why Traders Use It
Alan Hull built the HMA in 2005 to solve the usual moving average problem: you either get a smooth line that lags, or a fast line that chops you up.
HMA uses weighted moving averages plus a square-root smoothing step, so it hugs recent price action but still looks clean on the chart.
In practice, traders like it because it tends to:
Cut lag: Reacts quicker than most SMA/EMA settings to turns and momentum shifts
Filter noise: Keeps a smooth curve so you’re not trading every random wick
Spot trend changes earlier: Helps with timing entries, exits, and trailing stops
Stay usable across styles: Fast enough for intraday, still stable enough for swing
It’s especially handy in fast markets (think Nasdaq names, index futures, liquid FX pairs) where a slow average leaves you late and a twitchy one gets you whipsawed.
The math is the reason it behaves differently, so it’s worth knowing what’s under the hood.
Hull Moving Average Trading Strategies: Entries, Exits, and Trend Filters
Dual HMA Crossover Strategy: How It Works
The dual-HMA crossover is the classic way traders use it.
You run a fast HMA against a slow HMA and trade the flips.
It’s still a moving-average system (so ranges can hurt), but HMA’s speed makes the signals feel less “late” than SMA/EMA crossovers.
A common pairing is a shorter HMA (9–12) versus a longer HMA (50+), depending on the instrument and timeframe.
Dual HMA Crossover Rules: Buy and Sell Signals
Buy Signal: Fast HMA crosses above slow HMA (bullish momentum picking up)
Sell Signal: Fast HMA crosses below slow HMA (momentum fading / trend rolling)
Trend Confirmation: In an uptrend, price holding above both HMAs usually keeps you out of weak longs; in a downtrend, price below both keeps shorts cleaner
Price vs HMA Crossover: Using One HMA as a Trigger
You can also treat a single HMA as the trigger line.
Price reclaiming the HMA can be a long cue; losing it can be an exit or short cue.
This tends to work best when the market is already trending, so it helps to confirm with something objective like a volume expansion, a break of a prior swing high/low, or a clean market structure shift.
How to Use HMA for Trend Following
As a filter, it’s straightforward: only take longs when price is above the HMA and the HMA is rising; only take shorts when price is below and the HMA is falling.
That one rule alone can save a lot of bad counter-trend trades when the tape is messy.
The slope matters.
A steep HMA angle usually means momentum is real.
When it flattens, the market is often rotating, and cross signals get less trustworthy.
Best HMA Settings by Timeframe (Scalping to Swing Trading)
Scalpers: 9 or 13 HMA on 1–5 minute charts
Day Traders: 16 HMA on 15–60 minute charts (or 9/13 if you want it faster)
Swing Traders: 50–55 HMA on daily charts
Best Indicators to Combine With HMA for Confirmation
HMA signals get better with confluence.
RSI can keep you from chasing extended moves.
MACD divergence can warn when a trend is losing fuel.
Volume spikes help validate that a crossover isn’t just a low-liquidity head fake.
Old-school support/resistance levels (prior day high/low, weekly VWAP areas, key swing points) add context the average can’t see.
Quants will backtest parameter sets, but discretionary traders can do the same thing in a practical way: test a few periods on one instrument, across trend and chop regimes, and keep what holds up.
Best HMA Period Settings for Scalping, Day Trading, and Swing Trading
The period you pick is the whole game.
Too short and you’ll get chopped to pieces in a range.
Too long and the line becomes “pretty but late,” especially on reversal days.
Hull’s commonly cited default is 16, which is a decent middle ground if you don’t have a strong reason to go faster or slower.
Recommended HMA Periods by Trading Style
Trading Style | Recommended Period | Timeframe | Purpose |
|---|---|---|---|
Scalping | 9-13 | 1-5 minutes | Fast triggers; very sensitive to micro swings |
Day Trading | 9, 13, or 16 | 5-minute charts | Catch intraday momentum without too much lag |
Swing Trading | 20, 50, or 55 | Daily charts | Hold trends, ignore smaller pullbacks |
Position Trading | 50-100 | Weekly charts | Big-picture trend bias and major dynamic S/R |
Shorter settings (9/13/16) are usually better for day trading, while 20/50/55 fits swing work.
The shorter you go, the faster it reacts and the more fakeouts you’ll see when the market is rotating.
The longer you go, the cleaner the trend read, but the later the turn.
One extra wrinkle: because HMA uses √n, period changes aren’t linear.
Moving from 9 to 16 doesn’t “feel” the same as moving from 50 to 57, even though it’s +7 in both cases.
Backtest on the actual instrument you trade.
A high-beta stock like NVIDIA won’t behave like the S&P 500 e-mini, and EUR/USD won’t behave like crude oil.
Tune the period to the volatility and the holding time you’re actually targeting.
Hull Moving Average Pros and Cons: When HMA Works (and When It Fails)
HMA Benefits: Reduced Lag and Smoother Trend Signals
HMA tends to shine most in trending conditions, where the reduced lag helps you stay with the move and the smoothness keeps you from bailing on every pullback.
Lag reduction is the headline: it usually reacts faster than comparable SMA/EMA settings.
Smoother structure makes trend reads and trailing decisions easier.
Flexible use means it can be a trigger line, a filter, or dynamic support/resistance.
Noise control helps reduce some whipsaw, and momentum visibility improves when you pay attention to slope and curvature.
For day traders and swing traders, that often translates into earlier entries on breakouts and cleaner exits on trend fades, especially when the market is moving with conviction.
HMA Drawbacks: False Signals, Whipsaws, and Parameter Sensitivity
It’s still a moving average, so it won’t save you in chop.
The main issues to plan around:
Parameter sensitivity: Period choice matters a lot, so you need testing
False signals in volatility: Big wicks and news spikes can still flip it
More complex behavior: Harder to “feel” than an SMA if you don’t know the mechanics
Whipsaws in ranges: Sideways markets can grind crossover systems down
Needs confirmation: Best used with structure, volume, and another momentum/condition filter
Used correctly, HMA is a strong component, not a complete system.
Keep risk rules tight (position sizing, predefined stop, clear invalidation), and use the HMA to support the trade idea—not to replace price action, liquidity, and context.
Hull MA vs SMA vs EMA: Lag, Smoothness, and Noise Filtering
Compared with an SMA or EMA, the HMA usually prints turns sooner and with a cleaner curve.
SMA is smooth but slow.
EMA speeds things up by weighting recent data, but it can still lag on sharp reversals.
HMA pushes that idea further with WMA stacking plus the square-root period, so it tends to “catch up” faster without becoming a choppy mess.
Key HMA Traits: Faster Signals and Cleaner Trend Lines
Responsiveness - Picks up reversals and momentum shifts earlier, which matters on breakouts and first pullbacks.
Curve Smoothness - Still draws a clean line you can actually use for structure, not a jagged zigzag.
Noise Filtering - Filters a lot of random back-and-forth so you’re not reacting to every small retrace.
How Reduced Lag Changes Entries, Exits, and Trailing Stops
Less lag means your trigger isn’t always late.
That can improve entries during trend starts, and it can also help you trail closer in strong moves.
The trade-off is you’ll still get chopped in ranges, just usually less than with a very fast EMA.
Does HMA Work on Different Timeframes?
HMA tends to read well from a 5-minute chart up to daily/weekly because the line stays smooth even when it’s responsive.
That makes it easier to align trend direction across timeframes without second-guessing every candle.
Metric | SMA | EMA | Hull MA |
|---|---|---|---|
Lag | High | Medium | Low |
Smoothness | Low | Medium | High |
Responsiveness | Low | Medium | High |
Noise Filtering | Medium | Medium | High |
Once you know how it behaves versus SMA/EMA, it’s easier to decide where it fits: trend filter, trigger line, or a trailing guide.
Hull Moving Average Formula: How Is HMA Calculated?
HMA(n) = WMA(2 × WMA(n/2) − WMA(n), √n).
That structure is basically a “speed up” step (the 2× half-length minus full-length) followed by a “smooth it without killing it” step (the √n WMA).
The nesting is what strips out a lot of lag while keeping the trend line readable.
HMA Calculation Steps (n/2 and √n)
The HMA is built in a few passes:
Calculate a WMA on half the period (n/2, rounded)
Calculate a WMA on the full period (n)
Compute: 2 × WMA(n/2) − WMA(n)
Run a final WMA on that result using √n (rounded)
How Weighted Moving Average (WMA) Weighting Works
WMA is the engine here.
Unlike an SMA where every candle gets the same vote, WMA leans harder on the most recent closes.
The common form is WMA(n) = Σ(i × Price(i)) / Σ(i), with Σ(i) = n(n+1)/2, so the newest bar has the biggest weight.
That’s why HMA can move fast without looking like a seismograph.
Why HMA Uses √n: Smoother Signals With Less Lag
The √n step is the “keep it smooth” part.
Because the smoothing window is shorter than n, you don’t reintroduce the same lag you just worked to remove.
Net result: less delay, fewer fake flips, and a line that still tracks structure.
HMA Example: 20-Period Hull Moving Average
For a 20-period HMA:
Calculate WMA(10) on closing prices
Calculate WMA(20) on closing prices
Compute: 2 × WMA(10) − WMA(20)
Apply WMA(4 or 5) to that result (since √20 ≈ 4.47)
What Makes HMA Unique vs EMA and SMA?
This layered setup is why HMA tends to turn earlier than an EMA while staying smoother than most “fast” averages.
It’s not magic, but it’s a solid upgrade if you want a trend line that reacts quickly without constantly baiting you into chop.
How do you turn HMA signals into repeatable improvements over time?
HMA can help you act sooner and filter noise, but the real edge comes from checking whether your chosen periods and rules actually hold up across trending and choppy regimes. After each session, log the exact setup (dual crossover vs single-line trigger), timeframe, HMA length, and what confirmation you used (structure, volume, RSI/MACD). Then review outcomes in terms of execution quality: did you enter on the intended signal, respect the invalidation level, and manage the trade according to the HMA slope/flattening cues discussed above? A consistent trading journal makes it easier to spot pattern-level issues like “too-fast settings in ranges” or late exits when the HMA flattens. Using a tracker with analytics—such as Rizetrade trading journal and performance analytics dashboard—helps organize PnL, win/loss by setup, and metrics by instrument so you can iterate on HMA parameters with evidence rather than memory.