Parabolic Weighted Moving Average (PWMA)

Overview

The Parabolic Weighted Moving Average takes the concept of linear weighting to its mathematical extreme by using squared weights instead of simple linear progression. While a standard WMA assigns weights of n, n-1, n-2, etc., the PWMA uses n², (n-1)², (n-2)², creating a parabolic curve of importance that heavily favors the most recent data. For example, in a 5-period PWMA, the weights would be 25, 16, 9, 4, 1 compared to 5, 4, 3, 2, 1 in a standard WMA. This dramatic difference in weighting creates an ultra-responsive indicator that reacts almost instantaneously to price movements.

The parabolic weighting scheme makes PWMA particularly effective for short-term trading and momentum strategies where catching moves early is crucial. The squared weights ensure that recent price action dominates the calculation, with older prices having negligible influence. This characteristic creates a moving average that hugs price action closely during trends while still providing some smoothing. However, this extreme sensitivity comes with increased susceptibility to whipsaws and false signals during choppy or ranging markets, making proper market condition assessment essential for effective use.

Interpretation & Trading Signals

Example Usage

Code examples will be available once the Rust implementation is complete.