Adaptive Oscillator Combining Trend, Mean Reversion, and Momentum

Summary

This indicator combines trend, mean reversion, and momentum scores into a bounded oscillator. Exponential moving averages, RSI, ATR, and momentum measures provide the inputs, while a Best-Worst Method model converts user comparisons of the three factors into normalized weights. Settings let users choose the most and least important factors and review the resulting weights and consistency guidance.

An optional adaptive layer updates how features are amplified using stored samples and an Adam-style optimization step. The displayed line can also be shifted by the learned component, with smoothing and signal-line crossovers used for visualization and alerts. The script describes its formulas and configurable components, but provides no performance results or evidence that the learning layer improves trading outcomes. Its alerts and oscillator readings should therefore be treated as indicator signals requiring independent testing, not as validated forecasts.

Key ideas

• The oscillator combines trend, mean-reversion, and momentum components using user-specified Best-Worst Method comparisons.
• A normalized set of factor weights is derived from the selected best and worst criteria and comparison values.
• An optional adaptive layer adjusts feature amplification and can shift the base oscillator line.
• A smoothed signal line, histogram, and crossovers provide visual cues and alert conditions.
• The document gives implementation details but no empirical evidence of profitability or predictive accuracy.

Tags

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