ATR Trailing Stops and Adaptive KAMA for Trend Confirmation

Summary

This strategy combines an ATR trailing stop with an adaptive Kaufman moving average (KAMA) filter to identify directional trends. The stop line scales with volatility and signals a bullish or bearish state based on price relative to the line. KAMA estimates directional efficiency by comparing net price movement with cumulative movement, then adjusts its smoothing response accordingly.

A long signal requires price above both indicators; a short signal requires price below both. The document describes default ATR settings and a KAMA length, but provides no reported backtest performance or evidence that the approach is profitable. It identifies likely limitations: lag during reversals, false signals in ranging markets, and sensitivity to parameter choices. It also notes that the described implementation lacks a clear exit plan and suggests out-of-sample validation, market regime filters, and additional exit rules.

Key ideas

• The ATR trailing stop adapts its distance from price to recent volatility.
• KAMA adjusts its smoothing based on the ratio of net movement to cumulative price changes.
• Signals require price to agree with both the ATR stop and KAMA direction.
• Ranging markets and delayed reversal responses may produce losses or late exits.
• Parameter tuning should be checked on forward or out-of-sample data.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.