What Is Kaufman’s Adaptive Moving Average (KAMA)?
Kaufman’s Adaptive Moving Average is an intelligent moving average tool developed on the Exponential Moving Average, which is responsive to trend volatility.
It follows the prices when the price fluctuations are insignificant, and the noise is low.
Developed by American quantitative financial theorist Perry J. Kaufman, the adaptive moving average not only takes into account the price action but also the market volatility.
How to Calculate Kaufman’s Adaptive Moving Average?
Kaufman is represented by:- KAMA(T1, T2, T3)
- T1 is the number of Efficiency Ratio(ER)
- T2 is the number of periods for the fastest EMA constant.
- T3 is the number of periods for the slowest EMA constant.
- ER = Change/Volatility
- Change = ABS(Close – Close (10 periods ago))
- Volatility = Sum10(ABS(Close – Prior Close))
- SC = [ER x (fastest SC – slowest SC) + slowest SC]2
Current KAMA = Prior KAMA + SC x (Price – Prior KAMA)
*Volatility is the sum of the absolute value of the last ten price changes (Close – Prior Close).
*The smoothing constant uses the ER and two smoothing constants based on an exponential moving average.
Why Use Kaufman’s Adaptive Moving Average?
When the market volatility is low, the Kaufman adaptive moving average (KAMA) remains near the current market price. However, when the volatility will increase, it will start lagging.
Therefore, one of the most significant advantages of the Kaufman adaptive moving average strategy is it can be used to identify the trend of current market price action. When it filters out the noise and shows specific trends, traders can use the information to exit and entry proficiently.
How To Use Kaufman’s Adaptive Moving Average Trading Strategy?
When the stock value increases, KAMA also increases indicating a bullish scenario.
When the stock value decrease KAMA also decreases indicating a bearish scenario.
Building KAMA Trading Strategy on Mudrex
To generate Buy/Sell signals two KAMA’s are compared with different Fastest time-period as the bigger fastest time period will show broader price volatility whereas the shorter fastest time-period will be for the more recent fluctuation. Thus, buying will be considered when longer time-perio crosses the shorter and vice-versa.
- BUY:- KAMA(12,6,24) > KAMA(12,3,24) OR EMA(9) > KAMA(15,5,30)
- SELL:- KAMA(12,6,24) < KAMA(12,3,24) OR EMA(9) < KAMA(15,5,30)
- Timeframe:- 3H
- Stop Loss:- 10%(Trailing)
Creating on Mudrex
Components:- To build the following strategy we will need 4 total compare blocks, i.e. 2 for buying and 2 for selling.
For buying, we will use the next 2 steps:-
For selling, we will use the next 2 steps:-
Running backtest on Binance Futures: BTC/USDT with tick interval of 3H yielded an overall profit of 71.85%
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