Adaptive Moving Average (AMA)
Last updated
Last updated
The Adaptive Moving Average (AMA), developed by Perry Kaufman, is a refined version of the traditional moving average. Unlike simple or exponential moving averages that use fixed periods, AMA adapts dynamically to market volatility and noise. Its goal is to provide a smoother and more responsive line that better reflects market conditions.
AMA intelligently adjusts its sensitivity: it reacts quickly to strong trends and slows down during sideways or choppy markets. This balance makes AMA a valuable tool for both trend-following and volatility-aware trading strategies.
The AMA incorporates two key components:
Efficiency Ratio (ER): Measures the smoothness or efficiency of price movement over a given period. It compares net price movement to total price movement, giving values between 0 (high noise) and 1 (strong trend).
Smoothing Constant (SC): This adjusts the responsiveness of the moving average. It’s based on the ER and determines how quickly the AMA adapts to market changes.
Where:
FastestSC and SlowestSC are constants related to the fastest and slowest EMAs allowed.
The result is squared to give the curve its adaptive behavior.
Once the SC is calculated, it is used in the following formula to derive the AMA:
The AMA behaves like a moving average line on your chart, but its shape changes depending on market conditions:
Sharp turns and strong trends: AMA will follow price closely, showing steeper slopes.
Consolidation or sideways markets: AMA flattens and smooths out, filtering out market noise.
Traders often use it similarly to other moving averages:
Price crossing above AMA may indicate a potential buy signal.
Price crossing below AMA may indicate a potential sell signal.
AMA can act as dynamic support or resistance during trends.
There’s no one-size-fits-all setting, but typical parameters include:
ER Period (Efficiency Ratio): 10
These settings allow AMA to remain responsive enough for active traders while filtering out noise.
However, traders can customize:
Shorter ER Periods for more responsiveness.
Longer ER Periods for more smoothing and trend confirmation.
Backtesting across different assets and timeframes is recommended to find optimal settings for your strategy.
AMA is versatile and can be used in different trading approaches:
When price stays consistently above a rising AMA, this suggests a bullish trend.
When price stays below a declining AMA, this suggests a bearish trend.
Entry signals can be generated on crossovers of price and AMA.
Use AMA to define the trend.
Enter on pullbacks to AMA in the direction of the trend (e.g., long trades during uptrends when price pulls back to AMA).
Pair AMA with RSI, MACD, or Momentum indicators to confirm strength or weakness.
For example: Buy when price is above AMA and RSI confirms bullish momentum.
Use AMA as a trailing stop in trending markets to lock in profits.
Overfitting the settings: Using overly optimized parameters might look great in backtests but fail in live markets.
Ignoring higher timeframes: AMA can provide misleading signals if broader market structure is not considered.
Trading every crossover: Not all price/AMA crossovers are valid trade signals—filter them with volume, structure, or confluence.
Relying on AMA alone: While powerful, AMA is best used in combination with other tools and context.
The Adaptive Moving Average (AMA) is a sophisticated tool that bridges the gap between trend detection and market noise filtering. Unlike traditional moving averages, AMA adjusts its behavior in real time, helping traders stay in strong trends while avoiding fake signals during consolidation.
While AMA is not a silver bullet, it can significantly improve decision-making when used correctly. Combine it with broader market context, other technical tools, and sound risk management to unlock its full potential.
Whether you’re trading crypto, stocks, or forex, the AMA deserves a spot in your toolkit for its flexibility, intelligence, and adaptability.
