Adaptive Lookback Averages Based on Market Swing Frequency

Summary

The document explains an adaptive lookback method for moving averages. It estimates a variable period by counting how many price bars are needed for a chosen number of swing highs or lows to form, then dividing the bar count by the swing count and rounding. A speed parameter adjusts how quickly the resulting average responds. The method is presented for simple, exponential, smoothed, and linear weighted averages.

The described behavior is a longer lookback in calmer or trending conditions and a shorter one in choppy, volatile conditions, where swings occur more frequently. The source suggests this design may suit short-term or counter-trend systems that need faster signals, while warning that trend-following systems could be more vulnerable to whipsaws. It gives a conceptual explanation, not empirical tests, and does not specify enough implementation details to establish profitability or robustness.

Key ideas

• The adaptive period is estimated from the bar frequency of a chosen number of price swings.
• A speed parameter modifies the responsiveness of the calculated lookback.
• The method shortens its lookback in choppy, volatile markets and lengthens it in calmer or trending markets.
• It can modify several common moving average types.
• The document presents a potential use for short-term and counter-trend systems but provides no performance tests.

Tags

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