Perry Kaufman Adaptive Moving Average (KAMA)

Hello to all our followers, today we bring you an article where we explain in detail a moving average indicator called KAMA.

This indicator was developed by Perry Kaufman, and is an adaptive moving average designed to take into account the volatility or “market noise”. The KAMA moving average approaches prices when price fluctuations are relatively small and noise is low. In addition, the KAMA will move away when price swings widen and follow prices from a greater distance. This trend following indicator can be used to identify the general trend, market inflection points, and to filter price movements.

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KAMA moving average calculation

For the calculation of the KAMA moving average there are several steps that are required. First we will start with the general configuration recommended by Perry Kaufman, which is KAMA (10,2,30).

  • 10 is the number of periods for the efficiency ratio (EER).
  • 2 is the number of periods for the fastest constant available for EMA.
  • 30 is the number of periods for the slowest constant available for EMA.

Before calculating the KAMA, we have to calculate the Efficiency ratio (ER) and the smoothing constant (SC). We are not going to go into details regarding the calculation of these components since there are modified indicators for platforms such as Metatrader 4 that allow us to calculate this moving average.

The final formula for the calculation of the KAMA is as follows:

KAMA = Prior KAMA + SC x (Price – Prior KAMA)

How is the KAMA indicator used?

Traders can use this moving average like any other trend following indicator, such as a traditional moving average. For example, they can look for price crosses above of below the KAMA line, changes in price direction and filtered signals.

First, a price crossing above or below the KAMA line indicates a possible change in market direction. As with any moving average, a simple moving average crossing system will generate a large number of signals and lots of false signals. Traders can reduce false signals by applying price action signals or a time filter for moving averages crossovers. For example, one requirement could be that price must sustain the crossover for a certain number of periods, or require the price to exceed KAMA by a certain percentage.

KAMA moving average

In addition, traders can use the KAMA address to define the general trend, which can be useful in trend following systems. This may require the  adjustment of some parameters to smooth the indicator even more. For example, traders can change the middle parameter, which is the fastest EMA constant, to smooth the KAMA and look for direction changes. The trend is bearish, as long as KAMA is falling and forming lower lows. The trend is bullish, as long as KAMA is increasing and setting higher highs.

Use of different combinations of the KAMA indicator to improve our analysis

Traders can also combine different trading signals and techniques in their operations. They can use a longer-term KAMA to define the larger trend and a short-term KAMA for intraday signals. For example, a KAMA (10,5,30) could be used as a trend filter and will be considered bearish as it decreases. Once we know that the trend is bearish, we could then look for bearish crosses of the price and the indicator in which the price moves below the KAMA (10,2,30).

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