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Kaufman’s Adaptive Moving Average (KAMA)

An indicator that accounts for both the volatility and direction of of the market

What is Kaufman’s Adaptive Moving Average (KAMA)?

The Kaufman’s Adaptive Moving Average (KAMA) was developed by American quantitative financial theorist Perry J. Kaufman in 1998. The technique began in 1972 but Kaufman officially presented it to the public through his book “Trading Systems and Methods.” Unlike other moving averages, Kaufman’s Adaptive Moving Average accounts not only for the market volatility but for the direction as well. It adjusts its length according to existing market conditions.

 

Kaufman’s Adaptive Moving Average

 

When market volatility is low, KAMA remains at its price, but when the volatility increases, it will remain behind. Traders generally use the moving average indicator to identify trends and reversals.

 

Calculating Kaufman Adaptive Moving Average

When calculating Kaufman Adaptive Moving Average, the following standard settings are used:

  • 10 – Number of periods for the Efficiency Ratio
  • – Number of periods for the fastest exponential moving average
  • 30 – Number of periods for the slowest exponential moving average

To obtain the value of the KAMA, you must first calculate the value of the Efficiency Ratio and the Smoothing Constant.

 

Step 1: Efficiency Ratio (ER)

The efficiency ratio shows the efficiency of price changes, and it fluctuates between 1 and 0. When the price remains unchanged over 10 periods, the ER is zero. However, if the price moves up or down 10 consecutive periods, the ER moves to 1. It is calculated by dividing the absolute difference between the current price and the price at the beginning of the period by the sum of the absolute difference between each pair of closes during the period. The formula for calculating ER is as follows:

ER = Change/volatility

Change = Absolute Value [Close – Close (past 10 periods)]

Volatility Sum = 10 periods (Close – Prior Close)

 

Step 2: Smoothing Constant (SC)

The smoothing constant is calculated for each period. It uses the value obtained for efficiency ratio and two smoothing constants as follows:

SC= [ER x (Fastest SC – Slowest SC) + Slowest SC]2

SC= [ER x (2/ (2+1) – 2/(30+1)) +2/ (30+1)]2

 

In the above equation, (2/30+1) is the smoothing constant for the recommended 30-period EMA. Also, the slowest smoothing constant is the SC for the slowest 30-period EMA, while the fastest smoothing constant is the SC for shorter 2-period EMA.

 

Step 3: KAMA

After getting the values of the efficiency function and smoothing constant, you can now calculate the KAMA indicator values. The formula is as follows:

KAMA= KAMAi-1 + SC x (Price – KAMA i-1)

 

Where:

  • KAMAi  is the value of the current period
  • KAMAi-1 is the value of the period preceding the period being calculated.
  • Price is the source price for the period being calculated.

 

How Kaufman’s Adaptive Moving Average Works

When traders use the KAMA indicator, they get a clear picture of the market behavior of the trends and make a trading decision based on the observation. The indicator uses historical data to obtain the final values, which means that it does not show future security trends and instead shows past trends. Traders make a decision on the basis that the trends will continue to develop in the same direction as the past trends and stay the same way into the future.

The KAMA indicator can also be applied to a chart. The trader enjoys the option of customizing the indicator, specifying its parameters in the properties dialog box. The main parameters to be customized include the calculation and appearance. The customer is required to specify the number of periods in the calculation parameter. The default number for the value is 14, but experienced traders can select any value between 2 and 1000.

When the KAMA indicator is represented on a chart, traders can analyze the behavior of the market and predict the direction of a trend. For example, the trader can identify the start of a new trend, the end of an old trend, and trend reversal points that can signal buying and selling patterns.

 

Uses of Kaufman’s Adaptive Moving Average

One of the uses of KAMA is to generate the general trend of the price action. Generally, when the KAMA indicator is moving lower, it indicates that the trend of going downwards. On the other hand, when the KAMA line is moving higher, it shows that the trend is going in an upward direction. Also, compared to the Simple Moving Average, KAMA offers fewer chances of generating false signals that may cause a trader to generate losses.

KAMA can also be used to spot the beginning of new trends and the trend reversal points. When a faster MA crosses above a slower MA, it indicates a change in the upwards direction. The trader can take a long position and close the trade when the two lines cross back. Typically, traders can generate trading signals when the KAMA lines crossover with price or other indicators.

 

Related Readings

CFI offers the Financial Modeling & Valuation Analyst (FMVA)™ certification program for those looking to take their careers to the next level. To keep learning and advancing your career, the following resources will be helpful:

  • Momentum Investing
  • Technical Analysis – A Beginner’s Guide
  • Trading Mechanisms
  • VIX

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