Using an Adaptive Super Smoother to Pre-Filter a Stochastic

Summary

The note describes an experimental indicator that applies an adaptive, variable-length Super Smoother to price data before calculating a stochastic oscillator. The filtering is intended to reduce price noise and produce a smoother signal that may help identify trends. The author considers the result potentially usable for trading, but provides no backtest, performance figures, or detailed signal rules.

Because smoothing can change how and when the oscillator reaches its extremes, the note sets its default overbought and oversold thresholds relatively far apart. It recommends trying different parameters for each instrument and timeframe and adjusting those thresholds to fit the trader’s approach. These suggestions are qualitative; the document does not specify parameter values, explain how the adaptive filter is calculated, or establish whether the indicator improves decisions or returns.

Key ideas

• The adaptive Super Smoother filters prices before the stochastic oscillator is calculated.
• The resulting oscillator is described as smooth enough to potentially assist with trend identification.
• The author suggests calibrating parameters to the instrument and timeframe.
• Overbought and oversold thresholds may need adjustment because the output is heavily smoothed.

Tags

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