> "Linear weighting is for people who think the world is flat. PWMA squares the weights, because recent data isn't just more important—it's exponentially more important."
PWMA (Parabolic Weighted Moving Average) applies a parabolic ($i^2$) weighting scheme to the data window. This assigns massive importance to the most recent data points while still technically including the older data. It's like a WMA on steroids.
While the WMA uses a linear triangle window ($1, 2, 3, \dots, n$), the PWMA uses a parabolic window ($1^2, 2^2, 3^2, \dots, n^2$). This was developed for traders who found the WMA too slow but the EMA too jittery. It provides a curve that turns faster than a WMA but is smoother than an EMA at the tail.
By maintaining these three sums, we can update the parabolic average by adding the new point and subtracting the trailing effects, without iterating over the window.
1.**Resync**: Because we use triple running sums, floating-point errors can accumulate faster than in a simple SMA. Our implementation automatically resyncs every 1000 ticks to maintain precision.
2.**Sensitivity**: This indicator is very sensitive to the most recent bar. It can "repaint" visually if used on an open bar (though the math is consistent).
