Super Smoother (2-Pole Filter)

Overview

The Super Smoother represents John Ehlers' application of digital signal processing to financial markets, specifically implementing a two-pole Butterworth filter design. Published in "Cybernetic Analysis for Stocks and Futures," this filter excels at removing market noise while preserving the underlying trend signal. The mathematical foundation uses coefficients derived from the cutoff period: a = exp(-1.414π/period) and b = 2a×cos(1.414π/period), creating a recursive filter that provides superior price following compared to the 3-pole version while maintaining excellent noise reduction.

What makes the Super Smoother particularly effective is its optimal balance between responsiveness and smoothing. The cutoff period parameter determines the maximum cycle period considered as noise - any price movements with periods shorter than this setting are filtered out. With approximately 1.5 bars of lag for a 10-bar cutoff period compared to 2 bars for a simple moving average, the Super Smoother delivers earlier signals while maintaining consistency during trends and reacting quickly to sudden price movements, making it an ideal baseline indicator for trend-following systems.

Interpretation & Trading Signals

Example Usage

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