Enhanced Oscillator Trigger: Filtered Oscillators and Regression Smoothing

Summary

The Enhanced Oscillator Trigger (EOT) combines three normalized oscillators with smoothing and regression-based components. Each oscillator applies a high-pass filter and a supersmoother to price-derived data, then uses a fast-attack, slow-decay peak estimate to normalize the filtered output. Different period and coefficient settings let the three components respond differently to market cycles. The article also describes an LSMAWT calculation that blends a trend-cycle measure, volume-based money flow, RSI, and linear regression smoothing. Optional Fibonacci reference levels and a trigger line provide additional visual context.

The text proposes using oscillator threshold crossings to spot possible reversals, and the smoothed components to assess trends and possible entries or exits. It gives parameter examples and implementation details, but no backtest, market-specific validation, or measured results. Thresholds and settings are configurable, so signals may vary with choices and time frame; the indicator’s suggested uses should be treated as hypotheses requiring independent testing.

Key ideas

• Three filtered oscillators use different settings to represent distinct market cycles.
• A decaying peak estimate normalizes each filtered oscillator’s output.
• The LSMAWT component combines trend-cycle, volume-flow, RSI, and regression-based smoothing calculations.
• Threshold crossings and reference levels are presented as possible aids to reversal and entry or exit assessment.
• The article provides no performance validation, so users need to test settings and signals independently.

Tags

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