An Adaptive RSI Calculated from Smoothed Prices

Summary

This note proposes calculating the Relative Strength Index from a filtered price series instead of raw prices. It suggests that smoothing can suppress some short-lived price fluctuations before they affect the RSI, while an adaptive lookback average can make the resulting oscillator responsive to changing conditions. Possible inputs include simple, exponential, smoothed, or linearly weighted moving averages.

The indicator also uses normalized zones to help judge the strength of an RSI reading and identify possible reversals or trend exhaustion. Suggested signal approaches are the slope of the indicator or crossings of selected levels, with experimentation to find appropriate parameters. The note gives no formula for normalization, parameter settings, market examples, or performance tests, so it presents an indicator concept rather than validated evidence that the method improves trading results. Any use would require testing across instruments and market regimes, including comparison with a conventional RSI.

Key ideas

• The indicator computes RSI from an averaged price series rather than raw prices.
• Smoothing is intended to reduce the effect of false signals at the input stage.
• Several moving average types can provide the filtered price series.
• Normalized zones are intended to help assess strength and possible exhaustion.
• Possible signals use the indicator slope or crossings of chosen levels.

Tags

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