✔️ Information reviewed and updated in May 2024 by Eduardo López
Technical indicators like the Adaptive Moving Average are very good at supporting, confirming and predicting price movements. Especially for traders, who have to strategize to make their investments work perfectly.
Thus, with the help of these indicators, traders can identify trends and signals within the market. A leading indicator can predict future price movements, while a lagging indicator looks at past trends.
The trader must use his knowledge and sense of risk to decide which is the trading indicator that will best suit his strategies. Bearing in mind that indicators can often work better when combined.
Today we will talk about the adaptive moving average indicator, one of the indicators that has evolved over time and is widely used by trading operators as it aims to provide answers to all their problems.
➡Definition of the adaptive moving average indicator
This indicator combines the advantages of slow and fast moving averages. It was developed by Perry Kaufman and described in his book "Smarter Trading".
It has a faster movement when the market is trending to offer signals with speed.
On the other hand, it has a slower movement when the market is in a fluctuation band, in order to filter noise. This indicator uses two smoothing constants, “SC Fast” and “SC Slow”.
➡What is the adaptive moving average for?
The adaptive moving average indicator is used to construct a moving average with sensitivity to noise in the price series, and is characterized by minimal delay in detecting a trend.
One of the disadvantages of price series algorithms is that some accidental price jumps can lead to false signals on the emergence of the trend. Also, the smoothing has a long signal delay over the trend stop or turn.
➡How is it obtained?
The adaptive moving average starts from an exponential moving average, in which your calculation has more weight in recent data so that you can give faster results to recent changes.
Its formula is the following: KAMA (Current) = previous KAMA + SC * (Price-Previous KAMA)
The author Perry Kaufman, decided to replace the variable weight with a constant that is based on the principle of efficiency. This with the purpose of measuring the strength of a trend within a given period of time.
In order to find this principle correctly, you must first obtain the Efficiency Ratio, which is the price change adjusted for daily volatility.
To obtain the average, a smoothing constant is used, this to smooth the Efficiency Ratio. Usually, the period of the moving average and the slow moving average is kept constant, and only the fast moving average changing.
➡What is the interpretation?
A bullish signal is obtained when the adaptive moving average indicator rises. On the contrary, a bearish signal is obtained when the indicator goes down.
