Stochastic Signals Using Adaptive Lookback Averages

Summary

This note proposes calculating a stochastic oscillator from an averaged price series instead of using raw prices directly. Smoothing the input is intended to filter some false moves before the oscillator is calculated, while an adaptive lookback average is said to make the resulting oscillator adaptive as well.

Possible input averages include simple, exponential, smoothed, and linearly weighted moving averages. The suggested signal approaches are the usual ones for a stochastic oscillator: follow its slope or watch for crossings of selected levels. The note gives no formula for the adaptive lookback, parameter settings, market examples, or backtest evidence, and advises experimenting with parameters. Its claimed reduction in false signals is therefore an unverified rationale rather than a demonstrated result.

Key ideas

• The oscillator is calculated from an averaged price series rather than raw prices.
• Smoothing is intended to filter false moves before oscillator calculation.
• The note lists four moving-average types for the input series.
• Suggested signals use oscillator slope or crossings of selected levels.
• No adaptive-lookback formula or empirical test results are provided.

Tags

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