Adaptive Trend Classification with Performance-Weighted Moving Averages

Summary

This indicator combines six moving-average families—EMA, Hull, WMA, DEMA, linear-regression, and Kaufman adaptive averages—into adaptive trend signals. It evaluates variants across selectable lengths and assigns weights based on generated equity. A configurable cutout can exclude early history, while decay reduces the influence of older performance and an exponential growth factor changes how strongly current and future performance affects weights. Threshold crossings produce long or short signals, and a strategy view shifts entries and exits by one bar for calibration and backtesting.

Inputs also control robustness ranges, average lengths, starting weights, and signal thresholds. Tables expose weights and warnings, and users can select which average drives coloring or alerts. The source describes a framework and its controls, but supplies no independent performance results, market-specific validation, or evidence that adaptive weights generalize. Since weights respond to historical equity, results may be sensitive to the chosen sample, settings, and cutout period; backtest signals should be checked for timing and robustness.

Key ideas

• The signal blends multiple moving-average types and lengths using weights linked to their generated equity.
• A cutout period, decay, and exponential growth settings control how historical and recent performance influence weights.
• Robustness-length choices and adjustable thresholds shape the classification and signal behavior.
• The script offers a one-bar-shifted strategy view, but the document provides no out-of-sample validation or performance evidence.

Tags

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