KAMA Indicator: Formula, Settings and How to Read It
KAMA (Kaufman Adaptive Moving Average, 1995) changes its own smoothing speed from bar to bar: when price travels in a straight line it follows closely, and when it oscillates it slows down. The adaptation is driven by an efficiency ratio comparing net movement to total movement over the lookback.
Senzoukria · Indicators · Updated September 2026
KAMA ships with the Senzoukria desktop app, in the Averages & volatility group of the indicator catalogue. It is drawn on the price chart.
What KAMA measures
The efficiency ratio is the absolute distance between the current close and the close N bars ago divided by the sum of the absolute bar-to-bar changes over the same span, so it approaches 1 for a direct move and 0 for a path that goes back and forth. When that sum is zero, meaning a perfectly flat window, the ratio is set to 0 and the average smooths maximally, a documented choice since a 0/0 has no direction. The smoothing factor is interpolated between the fast and slow settings by that ratio and the result is then squared. The series is seeded with the raw close at bar N - 1, Kaufman's convention, and then follows KAMA = previous + SC x (close - previous).
The formula, as implemented
This is not a description of how the indicator is usually defined elsewhere — it is what the shipped code computes, documented next to the implementation:
KAMA — Kaufman Adaptive MA (Kaufman, 1995) : ER[i] = |close[i] − close[i−N]| / Σ_{j=i−N+1..i} |close[j] − close[j−1]| (Σ = 0 → ER = 0 : marché parfaitement plat, lissage maximal — choix documenté, le 0/0 n'a pas de direction) SC[i] = ( ER·(2/(fast+1) − 2/(slow+1)) + 2/(slow+1) )² KAMA[N−1] = close[N−1] (graine = prix brut, convention Kaufman ; nulls avant) KAMA[i] = KAMA[i−1] + SC·(close[i] − KAMA[i−1]) pour i ≥ N Défauts N=10, fast=2, slow=30 (les défauts historiques de Kaufman).
How to read it
- A KAMA that goes flat is reporting a collapsed efficiency ratio, that is, a market that covered a lot of distance without going anywhere.
- A KAMA that hugs price reports the opposite, and that is the phase in which its distance from price is worth measuring.
- Squaring the interpolated factor makes the response non-linear in the efficiency ratio: the line stays near its slow end across most of the range and only speeds up as the ratio approaches 1.
- A price cross of a flat KAMA is a weak event by construction, while the same cross while the line is accelerating carries more of the data behind it.
- Putting a fixed-period average of the same length next to it shows when the adaptation actually engaged.
Parameters and defaults
The defaults are an efficiency ratio period of 10 with fast 2 and slow 30, Kaufman's original set. Fast and slow are written as EMA periods and define the two ends of the interpolation, but since the interpolated factor is squared, the line is always slower than the EMA those periods suggest, and markedly slower at the slow end. The efficiency ratio period decides over how many bars directness is measured, and shortening it makes the adaptation itself twitchier.
| Parameter | Type | Default | Range |
|---|---|---|---|
| ER period | number | 10 | 1 – 200 |
| Fast EMA | number | 2 | 1 – 50 |
| Slow EMA | number | 30 | 2 – 200 |
What it does not show
The efficiency ratio only compares net travel to total travel over the window, so a market that trends steadily with deep pullbacks scores low and gets smoothed as if it were going nowhere. The seed is a raw close, which lets one unrepresentative bar pull the first plotted values until the recursion settles. Adaptation reduces whipsaw without removing lag, and at the slow end the line is deliberately late. As with every average in this group, only closes enter the calculation, so the bid and ask composition of the volume that produced them stays outside its scope.
Using it in Senzoukria
Add it from the Indicators panel of any footprint chart or candle chart. It runs on futures data from Rithmic or Databento and on crypto pairs from Binance and Bybit, on the same engine — the calculation does not change with the venue, only the data feeding it does. Market data subscriptions are billed by the provider, separately from the app.
Related indicators
- SMA — Averages & volatility
- EMA — Averages & volatility
- WMA — Averages & volatility
- Hull MA — Averages & volatility
- ATR (Wilder) — Averages & volatility
- Bollinger — Averages & volatility
See the full indicator library, or start with the order flow guide if you are new to reading aggression, delta and absorption.
Frequently asked questions
- What is the efficiency ratio in KAMA?
- It is the net price change over N bars divided by the sum of the absolute changes of each bar in that span. A value near 1 means price moved almost in a straight line, a value near 0 means it travelled a long path for little net result. KAMA uses it to pick a smoothing speed between its fast and slow settings.
- How does an adaptive moving average differ from a normal one?
- A fixed moving average applies the same weighting whatever the market is doing. KAMA recomputes its smoothing factor at every bar, so one set of settings produces a fast line during a directional move and a slow one during choppy trade.
- What do the fast and slow parameters do in KAMA?
- They are the two ends of the adaptation, written as EMA periods, with defaults of 2 and 30. The efficiency ratio interpolates a factor between them and that factor is then squared, which pulls the line toward the slow side over most of the range: at the low end it smooths considerably more than an EMA of 30 would, and at the high end it stays somewhat slower than an EMA of 2.