Kaufman Adaptive Moving Average (KAMA)
The Smart MA That Speeds Up in Trends and Chills Out in Chop
Back in 1995, trading wizard Perry J. Kaufman dropped a game-changer in his book *Smarter Trading*: the Kaufman Adaptive Moving Average (KAMA). Tired of fixed-length moving averages that either lag like a turtle in strong trends or jitter like a caffeinated squirrel in sideways markets? KAMA fixes that by automatically adjusting its own responsiveness every single bar. It snuggles close to price when the market's trending cleanly and freezes up when it's just noisy drifting. Genius, right? It's the thinking trader's moving average.
How KAMA Thinks – The Adaptive Magic Step by Step
KAMA isn't complicated once you break it down:
- Efficiency Ratio (ER): Measures how 'directional' price has been over the last n periods. ER = |Change over n| / Sum of absolute bar changes. Straight-line move? ER ≈ 1. Total mess? ER ≈ 0.
- Smoothing Constant (SC): Blends a fast constant (e.g., for 2-period EMA) and slow constant (e.g., for 30-period EMA). SC = [ER × (fastSC – slowSC) + slowSC]² – the square makes it even more responsive at extremes.
- KAMA Update: Just like an EMA: KAMAₜ = KAMAₜ₋₁ + SC × (Priceₜ – KAMAₜ₋₁). Starts seeded with a simple SMA.
Result? When ER is high (strong trend), SC gets fast and KAMA hugs price tightly. When ER is low (noise), SC shrinks and KAMA barely budges – acting like a much longer average.
Classic settings: ER period=10, fast=2 (SC≈0.666), slow=30 (SC≈0.0645). Tweak if your market is hyper-fast or glacial.
Reading KAMA's Mood – What the Line Tells You
Simple but powerful signals:
- ER near 1: Clean direction – KAMA tracks price closely, great dynamic support/resistance.
- ER near 0: Pure noise – KAMA flattens out, warning you to stay away or switch tactics.
- Upward slope: Uptrend mode – price above rising KAMA = bulls in charge.
- Downward slope: Downtrend – price below falling KAMA = bears ruling.
It's like having a trend strength meter built right into your moving average.
Battle-Tested Ways to Trade KAMA
Practical setups traders love:
- Trend filter: Go long only when price > KAMA and KAMA sloping up; short when price < KAMA and sloping down.
- Crossover plays: Pair a fast KAMA (short ER, quick params) with a slower traditional MA – trade the crosses.
- Pullback hunter: In a confirmed uptrend, buy dips that touch KAMA and bounce (close back above); stop just below recent low or 1×ATR.
- Position sizing boost: Use ER as a throttle – bigger positions when ER > 0.6 (strong trend), smaller or flat when ER < 0.3.
Always confirm with volume, higher timeframe, or an oscillator – KAMA shines brightest with friends.
The Good, the Tricky, and the Occasional Freeze
Strengths
- Self-adjusting magic – automatically faster in trends, calmer in chop.
- Fewer whipsaws than fixed EMAs of similar average speed.
- Only three easy parameters, yet robust across many markets.
Caveats
- Parameter sensitivity – too aggressive slow length makes it twitchy; too conservative adds lag.
- Can 'freeze' in ultra-low volatility (ER≈0) – some coders add a minimum SC floor.
- Sudden gaps or news spikes still cause overshoots before it adapts.
Your KAMA Setup Checklist
- Pick parameters matching your asset's personality (default 10,2,30 works for most).
- Align with higher-timeframe trend for context.
- Define risk first – stops beyond structure or ATR-based.
- Backtest across trending and ranging periods.
- Consider adding ER-based filters for position sizing or signal strength.
Key Takeaways
KAMA dynamically tunes itself: tight to price in strong trends, flat and patient in noise.
Solves the eternal MA dilemma – lag vs whipsaws – better than fixed averages.
Excellent as adaptive trend filter, dynamic S/R, or crossover component.
Watch parameter choice and low-volatility freezes – no tool is flawless.
Deploy with confirmation and solid risk rules – a dialed-in KAMA can make trend riding feel almost automatic. Stay adaptive and trade sharp!
Kaufman Adaptive Moving Average (KAMA)
The Smart MA That Speeds Up in Trends and Chills Out in Chop
Back in 1995, trading wizard Perry J. Kaufman dropped a game-changer in his book *Smarter Trading*: the Kaufman Adaptive Moving Average (KAMA). Tired of fixed-length moving averages that either lag like a turtle in strong trends or jitter like a caffeinated squirrel in sideways markets? KAMA fixes that by automatically adjusting its own responsiveness every single bar. It snuggles close to price when the market's trending cleanly and freezes up when it's just noisy drifting. Genius, right? It's the thinking trader's moving average.
Table of Contents
How KAMA Thinks – The Adaptive Magic Step by Step
KAMA isn't complicated once you break it down:
- Efficiency Ratio (ER): Measures how 'directional' price has been over the last n periods. ER = |Change over n| / Sum of absolute bar changes. Straight-line move? ER ≈ 1. Total mess? ER ≈ 0.
- Smoothing Constant (SC): Blends a fast constant (e.g., for 2-period EMA) and slow constant (e.g., for 30-period EMA). SC = [ER × (fastSC – slowSC) + slowSC]² – the square makes it even more responsive at extremes.
- KAMA Update: Just like an EMA: KAMAₜ = KAMAₜ₋₁ + SC × (Priceₜ – KAMAₜ₋₁). Starts seeded with a simple SMA.
Result? When ER is high (strong trend), SC gets fast and KAMA hugs price tightly. When ER is low (noise), SC shrinks and KAMA barely budges – acting like a much longer average.
Classic settings: ER period=10, fast=2 (SC≈0.666), slow=30 (SC≈0.0645). Tweak if your market is hyper-fast or glacial.
Reading KAMA's Mood – What the Line Tells You
Simple but powerful signals:
- ER near 1: Clean direction – KAMA tracks price closely, great dynamic support/resistance.
- ER near 0: Pure noise – KAMA flattens out, warning you to stay away or switch tactics.
- Upward slope: Uptrend mode – price above rising KAMA = bulls in charge.
- Downward slope: Downtrend – price below falling KAMA = bears ruling.
It's like having a trend strength meter built right into your moving average.
Battle-Tested Ways to Trade KAMA
Practical setups traders love:
- Trend filter: Go long only when price > KAMA and KAMA sloping up; short when price < KAMA and sloping down.
- Crossover plays: Pair a fast KAMA (short ER, quick params) with a slower traditional MA – trade the crosses.
- Pullback hunter: In a confirmed uptrend, buy dips that touch KAMA and bounce (close back above); stop just below recent low or 1×ATR.
- Position sizing boost: Use ER as a throttle – bigger positions when ER > 0.6 (strong trend), smaller or flat when ER < 0.3.
Always confirm with volume, higher timeframe, or an oscillator – KAMA shines brightest with friends.
The Good, the Tricky, and the Occasional Freeze
Strengths
- Self-adjusting magic – automatically faster in trends, calmer in chop.
- Fewer whipsaws than fixed EMAs of similar average speed.
- Only three easy parameters, yet robust across many markets.
Caveats
- Parameter sensitivity – too aggressive slow length makes it twitchy; too conservative adds lag.
- Can 'freeze' in ultra-low volatility (ER≈0) – some coders add a minimum SC floor.
- Sudden gaps or news spikes still cause overshoots before it adapts.
Your KAMA Setup Checklist
- Pick parameters matching your asset's personality (default 10,2,30 works for most).
- Align with higher-timeframe trend for context.
- Define risk first – stops beyond structure or ATR-based.
- Backtest across trending and ranging periods.
- Consider adding ER-based filters for position sizing or signal strength.
Key Takeaways
KAMA dynamically tunes itself: tight to price in strong trends, flat and patient in noise.
Solves the eternal MA dilemma – lag vs whipsaws – better than fixed averages.
Excellent as adaptive trend filter, dynamic S/R, or crossover component.
Watch parameter choice and low-volatility freezes – no tool is flawless.
Deploy with confirmation and solid risk rules – a dialed-in KAMA can make trend riding feel almost automatic. Stay adaptive and trade sharp!
Related Terms
Apply This Knowledge
Ready to put Kaufman Adaptive Moving Average (KAMA) into practice? Use our tools to analyze your portfolio and explore market opportunities.
This content is also available on our main website for public access.