Kaufman's Adaptive Moving Average (KAMA)

It is a moving average that adjusts its sensitivity to market conditions, aiming to provide a more accurate representation of price trends.



3/19/20244 min read

chart trading
chart trading

Kaufman's Adaptive Moving Average (KAMA)

Kaufman's Adaptive Moving Average (KAMA) is a technical indicator developed by Perry J. Kaufman. It is a moving average that adjusts its sensitivity to market conditions, aiming to provide a more accurate representation of price trends. KAMA is designed to reduce lag and noise, making it a valuable tool for traders seeking to identify and follow trends.

Biography of Perry J. Kaufman

Perry J. Kaufman is a well-known figure in the world of algorithmic trading and technical analysis. He has more than 40 years of experience in the financial industry and has authored several books on trading and investing. Kaufman is known for his innovative approach to market analysis and his expertise in developing trading systems and indicators.


The formula for calculating KAMA involves three main components: efficiency ratio (ER), smoothing constant (SC), and the previous KAMA value. The efficiency ratio measures the trendiness of the price series, with values closer to 1 indicating a strong trend. The smoothing constant determines the rate at which the moving average adapts to changes in market conditions.

KAMA = Previous KAMA + SC * (Price - Previous KAMA)

The smoothing constant is calculated using the efficiency ratio:

SC = (ER * (Fastest SC - Slowest SC)) + Slowest SC

The values for the fastest and slowest smoothing constants are typically set to 2 and 30, respectively.

How to Use KAMA

KAMA can be used in various ways to analyze price trends and generate trading signals. Here are a few common approaches:

1. Trend Identification

KAMA can help identify the direction of the prevailing trend. When the KAMA line is rising, it indicates an uptrend, while a declining KAMA line suggests a downtrend. Traders can use this information to align their trades with the overall market trend.

2. Entry and Exit Signals

KAMA can be used to generate entry and exit signals. When the price crosses above the KAMA line, it may be a signal to enter a long position. Conversely, when the price crosses below the KAMA line, it may indicate a signal to exit a long position or enter a short position. Traders can combine these signals with other technical indicators or price patterns to increase their confidence in the trade.

3. Support and Resistance Levels

KAMA can also act as dynamic support and resistance levels. Traders can use the KAMA line as a reference point to identify potential areas of buying or selling pressure. When the price approaches the KAMA line from below, it may find support, while a move towards the KAMA line from above may encounter resistance.

Combining KAMA with Other Indicators

KAMA can be combined with other technical indicators to enhance its effectiveness. Here are a few examples:

1. Moving Average Crossover

Traders can use a moving average crossover strategy in combination with KAMA. For example, when the shorter-term moving average crosses above the longer-term moving average and the price is above the KAMA line, it may indicate a bullish signal. Conversely, when the shorter-term moving average crosses below the longer-term moving average and the price is below the KAMA line, it may suggest a bearish signal.

2. Oscillators

Oscillators, such as the Relative Strength Index (RSI) or Stochastic Oscillator, can be used alongside KAMA to confirm trading signals. When KAMA generates a buy signal, a bullish confirmation from an oscillator can provide additional confidence in the trade. Similarly, a sell signal from KAMA combined with a bearish confirmation from an oscillator can strengthen the validity of the signal.

3. Price Patterns

Traders can also combine KAMA with price patterns, such as triangles or double tops/bottoms, to identify potential reversals or continuation patterns. When KAMA aligns with a significant price level or a pattern breakout, it can provide a stronger signal for traders.

Advice to Algorithmic Traders

For algorithmic traders, KAMA can be a valuable tool in developing trading strategies. Here are a few tips:

1. Optimize Parameters

Experiment with different values for the smoothing constants and other parameters to find the optimal settings for your trading strategy. Backtest your strategy using historical data to evaluate its performance under different market conditions.

2. Combine with Other Indicators

Consider combining KAMA with other indicators that complement its strengths and weaknesses. This can help filter out false signals and improve the overall accuracy of your trading strategy.

3. Monitor Market Conditions

Keep a close eye on market conditions and adjust your trading strategy accordingly. KAMA is designed to adapt to changing market dynamics, but it is still important to monitor its performance and make necessary adjustments when needed.


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