TrendLagging adaptive trend-smoothing indicatorKAMA

Kaufman Adaptive Moving Average KAMA

A moving average that speeds up in trends and slows down in noise, automatically.

Quick answer: The Kaufman Adaptive Moving Average, devised by Perry Kaufman, automatically adjusts its smoothing speed based on market efficiency — reacting fast when price trends cleanly and slowing to filter noise when price is choppy.

In simple words

Fixed moving averages have one speed, which is always wrong somewhere — too slow in a fast trend, too jumpy in a range. Kaufman's KAMA adapts: it measures how 'efficient' price movement is (how much net direction there is versus back-and-forth noise), then speeds up when a clean trend is underway and slows almost to a standstill when the market is chopping sideways. The effect is a line that follows trends closely yet stays flat and calm during noise, reducing whipsaw.

Kaufman Adaptive Moving Average — visual

How Kaufman Adaptive Moving Average looks on a chart

KAMA adapts its speed to market efficiency: it hugs price in clean trends and flattens out in choppy noise, cutting the whipsaw of fixed-speed averages.

Professional explanation

The Efficiency Ratio at its core

KAMA is built around Kaufman's Efficiency Ratio (ER): the net price change over N bars divided by the sum of the absolute bar-to-bar changes over the same period. When price moves in a straight line, net change nearly equals total travel, so ER is near 1 (efficient). When price chops back and forth, net change is small relative to total travel, so ER is near 0 (inefficient). ER is the dial that tells KAMA how fast to move.

From efficiency to a variable smoothing constant

KAMA converts the ER into a smoothing constant that sits between the speed of a fast EMA (about 2 periods) and a slow EMA (about 30 periods). High efficiency pushes the constant toward the fast end so KAMA tracks the trend; low efficiency pushes it toward the slow end so KAMA barely moves. Because the constant is squared, the shift between fast and slow is pronounced, giving KAMA its distinctive stop-and-go behaviour.

Why it reduces whipsaw

The whole point is to solve the range problem. In a sideways market a normal average crosses price repeatedly and whipsaws; KAMA, sensing low efficiency, flattens out and stops chasing every wiggle, so far fewer false crosses occur. When a genuine trend begins, efficiency rises and KAMA accelerates to catch it. This adaptiveness is what sets it apart from SMA, EMA and WMA.

Reading and trading KAMA

KAMA is traded like a moving average but with extra meaning in its slope: a flat KAMA signals a noisy, trendless market to avoid, while a sloping KAMA signals a trend worth trading. Price crossing a rising KAMA, or KAMA turning up, are the common signals. Because it deliberately slows in noise, it lags more than a fast EMA at the very start of a move — the trade-off for its whipsaw reduction.

Formula

Kaufman Adaptive Moving Average formula

KAMAₜ = KAMAₜ₋₁ + SC × (Priceₜ − KAMAₜ₋₁); SC = [ER × (fast − slow) + slow]²

ER = |net change over N| / Σ|bar-to-bar change over N|. fast and slow are the EMA smoothing constants for 2 and 30 periods. SC is the adaptive smoothing constant.

ER — Efficiency Ratio — net directional change divided by total price travel over N bars
SC — Smoothing Constant — the adaptive speed derived from ER, squared
fast — Smoothing constant of a fast EMA, 2/(2+1)
slow — Smoothing constant of a slow EMA, 2/(30+1)
N — Efficiency Ratio look-back, commonly 10

How it is calculated

Compute the Efficiency Ratio: net price change over N bars divided by the sum of absolute bar-to-bar changes over N.
Scale ER between the fast (2-period) and slow (30-period) EMA smoothing constants.
Square the scaled value to get the adaptive smoothing constant SC.
Update KAMA = previous KAMA + SC × (current price − previous KAMA).
Plot KAMA; a flat line means noise to avoid, a sloping line means a tradable trend.

Interpretation & signals

Traders read KAMA's slope as a regime filter — flat means choppy and best avoided, sloping means a trend to trade — and use price crossing KAMA or KAMA turning as the signal.

Buy / bullish signals

KAMA turns up and price holds above it.
Price crosses above a rising KAMA after it flattens in a base.
KAMA slope steepens as efficiency rises, confirming a new trend.
A faster KAMA crosses above a slower KAMA.

Sell / bearish signals

KAMA turns down and price holds below it.
Price crosses below a falling KAMA after a topping range.
KAMA slope steepens downward as a downtrend gains efficiency.
A faster KAMA crosses below a slower KAMA.

False signals to beware

When KAMA is flat, any price crosses of it are noise to be ignored.
At the very start of a move KAMA lags because efficiency has not yet risen.
In a weak, semi-trending market KAMA can give ambiguous, shallow slopes.

Settings, timeframe & conditions

Best settings

10 for ER, 2 and 30 for fast/slow (Kaufman defaults)

Avoid

Trading crosses when KAMA is flat (low efficiency)

Works best in

Markets that alternate between clean trends and chop

Struggles in

Persistent low-efficiency drift with no clean trend

Advantages & limitations

Advantages

Adapts speed to conditions, cutting whipsaw in ranges.
Hugs price in clean trends yet flattens in noise.
The slope doubles as a trend-versus-noise filter.
Reduces the false crosses that plague fixed averages.

Limitations & disadvantages

More complex to compute and understand.
Lags at the very start of a trend while efficiency builds.
Ambiguous in weak, semi-trending markets.
Parameters need tuning to the instrument.

Combining Kaufman Adaptive Moving Average with other indicators

Average Directional Index — ADX and KAMA both distinguish trend from range; a rising ADX with a sloping KAMA is strong trend confirmation.
Average True Range — ATR sizes stops around KAMA, adapting the exit to the same volatility KAMA is reacting to.
Exponential Moving Average — Comparing KAMA with a fixed EMA highlights when the market shifts from noise to trend.

Practical examples (Nifty & Bank Nifty)

NIFTY example

Nifty spends two weeks chopping in a 200-point band and KAMA goes almost flat — its low efficiency reading tells the trader to stand aside, avoiding the whipsaws a fixed EMA would have generated. When Nifty finally breaks out and trends cleanly, efficiency jumps, KAMA accelerates and slopes up, and price holding above the rising KAMA signals the trend is now worth trading.

BANKNIFTY example

Bank Nifty's frequent noisy swings are exactly what KAMA is designed for. During a choppy, newsy session KAMA flattens and filters out the fake breaks; when a decisive trending move develops, KAMA speeds up to track it. A trader uses KAMA's slope as a green light — trade only when it is clearly sloping, sit out when it is flat.

Common mistakes

Trading price crosses when KAMA is flat — those are the noise it is filtering.
Expecting it to be fast at a trend's very start — it lags until efficiency rises.
Using default parameters without checking they suit the instrument.
Treating it as just another EMA and ignoring its adaptive slope.

Professional usage

Professionals use KAMA primarily as an adaptive trend filter that answers 'is this a trend worth trading?'. When KAMA is sloping, efficiency is high and they engage; when it is flat, they stand aside, avoiding the range whipsaws that punish fixed averages. It is often combined with a volatility-based stop and a trend-strength gauge, valued less for precise entries than for keeping a trader out of the choppy conditions where most moving-average losses occur.

Key takeaway

KAMA is a self-adjusting moving average: it speeds up to track clean trends and slows almost to a stop in noise, cutting the whipsaw of fixed averages. Read its slope as a filter — trade when KAMA is sloping, stand aside when it is flat.

Frequently asked questions

What is the Kaufman Adaptive Moving Average?

KAMA is an adaptive moving average by Perry Kaufman that adjusts its smoothing speed to market conditions — reacting fast in clean trends and slowing to filter noise in choppy markets. It aims to cut the whipsaw of fixed-speed averages.

How does KAMA adapt?

It uses an Efficiency Ratio — net price change divided by total price travel over N bars — to gauge how trendy the market is, then speeds up when efficiency is high and slows down when it is low. The efficiency reading is the dial controlling its speed.

What is the Efficiency Ratio in KAMA?

The Efficiency Ratio is the net directional change over N bars divided by the sum of the absolute bar-to-bar changes over the same span. A value near 1 means a clean trend; near 0 means choppy noise.

What are the default KAMA settings?

Kaufman's defaults are a 10-period Efficiency Ratio with fast and slow smoothing constants based on 2- and 30-period EMAs. These can be tuned to the instrument and timeframe.

How is KAMA different from the EMA?

An EMA has a single fixed speed, while KAMA varies its speed with market efficiency — fast in trends, slow in noise. This adaptiveness is what reduces KAMA's whipsaw compared with a fixed EMA.

How do you trade KAMA?

Trade with KAMA's slope: when it is sloping the market is trending and worth trading, and when it is flat the market is choppy and best avoided. Price crossing a rising KAMA or KAMA turning up are common signals.

Does KAMA reduce whipsaw?

Yes, that is its main purpose — by flattening in low-efficiency, choppy markets it stops chasing every wiggle, producing far fewer false crosses than a fixed moving average.

Is KAMA a leading indicator?

No, KAMA is a lagging adaptive average. It actually lags a little at the very start of a trend, until efficiency rises and it accelerates to catch up.

Who created KAMA?

KAMA was developed by Perry J. Kaufman, who introduced it in his trading systems work; it is described in his book Trading Systems and Methods.

Can KAMA be used on Bank Nifty?

Yes, and Bank Nifty's alternation between noisy chop and clean trends is well suited to KAMA, which filters the noise and accelerates in the trends. Parameters may need tuning for its volatility.

Why is KAMA flat sometimes?

A flat KAMA means the Efficiency Ratio is low — price is chopping with little net direction — so KAMA deliberately slows down and stops following the noise. It is a signal to stand aside.

Voice search & related questions

Natural-language questions people ask about Kaufman Adaptive Moving Average.

What is KAMA in simple words?

KAMA is a smart moving average that moves quickly when the market is trending cleanly and slows down when the market is just chopping around, which cuts down on false signals.

How is KAMA different from a normal moving average?

A normal moving average has one fixed speed, while KAMA changes its speed automatically based on how trendy or noisy the market is.

When should I trade with KAMA?

Trade when KAMA is clearly sloping, which means a real trend is underway, and stand aside when it is flat, which means the market is choppy.

Who invented KAMA?

It was created by Perry Kaufman, a well-known trader and author, as an adaptive alternative to fixed moving averages.

Sources & references

Last reviewed 8 July 2026. Educational content only — not investment advice.