Supersmoother 3-Pole Filter

Parameters: period = 15 (5–50)

Overview

The 3-Pole Supersmoother Filter represents an evolution in digital signal processing applied to financial markets. Unlike the 2-pole version which provides a better approximation of price action, the 3-pole variant prioritizes superior smoothing characteristics, making it the filter of choice when maximum noise reduction is required. The filter implements a recursive calculation using coefficients derived from the cutoff period, incorporating the previous three filtered values to produce exceptionally smooth output that clearly reveals underlying trends.

The mathematical foundation of the 3-pole filter involves complex coefficient calculations using exponential and trigonometric functions. The filter formula uses four coefficients (coef1 through coef4) calculated from the cutoff period, with a1 = exp(-π/Period) and b1 = 2×a1×cos(1.738×180/Period). This sophisticated approach creates an Infinite Impulse Response (IIR) filter that can be used anywhere a moving average would traditionally be applied, but with substantially less lag for equivalent smoothing - approximately 1.5 bars for a 10-bar cutoff period compared to 2 bars of lag for a simple moving average.

Interpretation & Trading Signals

Trend Identification:

  • Rising Filter Line: Clear uptrend indication when line slopes upward
  • Falling Filter Line: Downtrend confirmed when line slopes downward
  • Direction Changes: Filter turning points signal potential trend reversals
  • Smooth Trends: Superior noise reduction reveals true market direction

Trading Applications:

  • Price Crossovers: Buy when price crosses above filter, sell below
  • Support/Resistance: Filter acts as dynamic support in uptrends
  • Cycle Detection: Best for detecting 30+ bar cycles
  • Multiple Timeframes: Consistent behavior across all chart periods

Filter Comparison:

  • vs 2-Pole: Better smoothing but slightly more lag
  • vs Moving Averages: Less lag with equivalent smoothing
  • Oscillator Base: Excellent foundation for custom indicators
  • Noise Reduction: Superior to traditional filters in noisy markets

Example Usage

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

Performance Analysis

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