KAMA Trend Strategy with Regime, RSI, and ATR Risk Filters

Summary

This strategy uses Kaufman’s Adaptive Moving Average (KAMA) as its trend signal, with configurable lookback and fast and slow smoothing lengths. A long setup requires KAMA to rise over a chosen interval, price to be above a simple moving average regime filter, and RSI to be above its midpoint. The short setup mirrors these conditions: falling KAMA, price below the regime average, and RSI below its midpoint. The visible logic closes an opposing position before considering a new entry and places a stop based on ATR multiplied by a configurable factor.

Position size is calculated from a selected percentage of account equity divided by the stop distance in point-value terms. The excerpt presents inputs and implementation logic, but gives no market, test period, performance results, or evidence that the risk calculation behaves consistently across instruments. It also ends partway through the short-entry logic, so the full exit and order handling cannot be assessed. The method should therefore be treated as a strategy design example rather than a validated system.

Key ideas

• KAMA direction is combined with a simple moving average regime filter and an RSI midpoint test.
• Long and short conditions use mirrored trend and momentum filters.
• ATR distance determines the stop level, and equity risk is used to calculate position size.
• The supplied excerpt contains no backtest results or instrument-specific evaluation.
• The code is truncated, leaving some short-side and exit behavior unshown.

Tags

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