Kaufman's Adaptive Moving Average (KAMA) - Multi timeframe

The Kaufman's Adaptive Moving Average (KAMA) - Multi timeframe indicator provides a trend-following line that dynamically adjusts its sensitivity based on market volatility and noise to reduce lag and filter out choppy price action.

Usage

The Usage section describes how the script can be used to identify trend direction while accounting for market conditions. Traders typically use KAMA to distinguish between significant price trends and insignificant market noise.

• Trend Identification: When the price is consistently above the KAMA line, it indicates a bullish trend; when below, it indicates a bearish trend.
• Filtering Market Noise: During periods of high volatility or "noise," the KAMA flattens out, helping traders avoid false signals in ranging markets. Conversely, when the market moves strongly in one direction, the KAMA follows the price more closely.
• Support and Resistance: The KAMA line can act as a dynamic level of support or resistance.
• Alerts: The script includes built-in alerts for price crossovers and crossunders, notifying the user when price action deviates from or returns to the adaptive average.

Details

The KAMA was developed by Perry Kaufman to solve the inherent lag found in traditional moving averages like the SMA or EMA. The core mechanism relies on Kaufman's Efficiency Ratio (ER), which measures the ratio of the net price change over a period relative to the sum of absolute price changes (the total path traveled).

If the ER is high (close to 1), it indicates a strong, efficient trend with little noise, causing the KAMA to become more sensitive. If the ER is low (close to 0), it indicates significant market noise or congestion, causing the KAMA to slow down and flatten. This adaptation allows the indicator to stay close to the price during trends but remain at a distance during volatile, non-directional movements.

This version also includes an experimental smoothing option using the least squares method (Linear Regression) to further refine the output and background coloring to visualize efficiency ratio thresholds.

Settings

• Lookback period: Sets the number of bars used to calculate Kaufman's Efficiency Ratio and the adaptive smoothing factor.
• Fill background: Low / High Noise: Enables or disables background coloring based on market noise levels.
• Low level of market noise: Selects the color for the background when the Efficiency Ratio is below the low threshold.
• High level of market noise: Selects the color for the background when the Efficiency Ratio is above the high threshold.
• Thresholds for Low / High Noise: Adjusts the Efficiency Ratio values (0 to 1) that trigger the background color changes.
• Smooth KAMA: When enabled, applies a Linear Regression (least squares) smoothing to the KAMA output over the specified lookback period.

FAQ

How does KAMA differ from a standard EMA? While an EMA uses a fixed smoothing constant, KAMA uses a variable smoothing factor that adjusts based on the Efficiency Ratio, making it faster during trends and slower during noisy periods.

What does it mean when the KAMA line is flat? A flat KAMA line indicates a period of high market noise or a sideways range where the price change is small relative to the total volatility, suggesting a lack of a clear trend.

How can I access the Kaufman's Adaptive Moving Average (KAMA) - Multi timeframe? You can get access on the LuxAlgo Library for charting platforms like TradingView, MetaTrader (MT4/MT5), and NinjaTrader for free.