FRAMA: Fractal-Dimension Estimation and Price-Range Choices
Summary
The document explains the Fractal Adaptive Moving Average (FRAMA) through an estimate of price-series fractal dimension. It divides a lookback into two equal intervals, measures each interval’s high-to-low range per bar, combines those measures with the range over the full lookback, and uses logarithms to estimate dimension. The resulting indicator is described as usable like other moving averages.
It also discusses an implementation choice: calculate ranges from sampled prices or from bar highs and lows. The author says the sampled-price option responds more quickly and better reflects the chosen calculation period. The text offers no performance tests or trading results to support that comparison, and it notes that descriptions of the original method can be ambiguous. It focuses on how to calculate and configure the indicator, rather than defining entry, exit, or risk rules.
Key ideas
- FRAMA estimates price fractal dimension from ranges measured across two equal lookback intervals and their combined span.
- The range-per-bar measures are combined using logarithms to derive the dimension estimate.
- The indicator can calculate ranges from sampled prices or from bar highs and lows.
- The author reports that using sampled prices makes the indicator more responsive, but provides no comparative test evidence.
- FRAMA is presented as usable in the same general way as other moving averages.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.