The AMA indicator is characterized by the minimum lag to detect a trend
indicator was developed and described by Perry Kaufman in his book - Smarter Trading
WADA indicator uses a ratio that compares the direction of the price with the calculated levels of volatility with Perry Kaufman algorithm.
The adaptive moving average (AMA) is a type of exponential moving average that uses a performance indicator to change the constant K = (2 ÷ (N + 1))
The moving average uses an indicator that compares the price with the level of volatility. It was designed to solve the problem of the choice between a fast moving average or slower. The moving average adaptation speed is automatically adjusted to the level of market volatility, and the moving average is moving slower on a market without trend (where prices move horizontally) and faster in a market with a better trend defined.
Read more about the rules and trading signals:
Exchange - Trading Kaufman Efficiency Ratio
Exchange - Trading Volatility Kaufman
Interpretation Signals And Rules Of Trading
The interpretation of the Adaptable Moving Average AMA is similar to a conventional moving average
- Buying Signals
. The price is above the moving average Adaptable AMA Moving Average - Bullish Signal
. The fast moving average crosses the slow upward moving average - bullish signal
- sell signal
. The price is below the moving average Adaptable AMA Moving Average - Bearish Signal
. The fast moving average crosses down the slow moving average - bearish signal
More:
. Trader Moving Average
characteristics Trading - Adaptive Moving Average AMA
. Provides parameters quantification of the price change
. Watch flipping points of the short-term trend
. Give the opportunity to understand the real strength and market trend
Formula - Adaptive Moving Average AMA
ER (i) = Signal (i) / Noise (i)
ER (i) - current value Efficiency Ratio
Signal (i) = ABS (price (i) - price (i - N)) - current value of the signal, absolute value of the difference between the current price and past price N periods
Noise (i) = Sum (ABS (price (i) - price (i-1)), N) - value of noise or current noise, sum of the absolute values of the difference between the current price and past price N periods
Analysis Trading
Trade Forex - Example
Currency Pair: EUR / USD
Time frame H1 - 1 Hour
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