WikiPG Scoring SystemEMA Smoothing & Recommendation Hysteresis (P2)

EMA Smoothing & Recommendation Hysteresis

PulseGrid v2.0 applies Exponential Moving Average (EMA) smoothing to raw PG scores and recommendation hysteresis to signal transitions, addressing two critical failure modes: signal noise and recommendation churn.

The Problem: Signal Churn

Without smoothing, the PG-MIM engine can oscillate between adjacent signals (e.g., SELL to HOLD to SELL) on consecutive days when the raw score hovers near a threshold boundary. This creates false signals and reduces user confidence.

EMA Smoothing

The EMA smoothing function applies a weighted average that gives more importance to recent scores while dampening short-term noise:

> EMA(t) = alpha Score(t) + (1 - alpha) EMA(t-1)

Where:

  • alpha = 2 / (halfLife + 1)
  • halfLife = 5 (configurable, default 5 data points)

The half-life of 5 means that a score from 5 periods ago carries approximately half the weight of the current score. This preserves trend direction while filtering out single-day spikes.

Recommendation Hysteresis

Hysteresis prevents oscillation by requiring a score to cross a threshold by a margin before changing the recommendation:

TransitionStandard ThresholdWith Hysteresis (margin = 3)
HOLD to BUYScore > 15Score > 18
BUY to HOLDScore < 15Score < 12
HOLD to SELLScore < -15Score < -18
SELL to HOLDScore > -15Score > -12

The hysteresis margin creates a "dead zone" around each threshold. Once a recommendation is established, the score must move further in the opposite direction to reverse it. This reduces false signal transitions by 15-25% based on backtesting.

Implementation

  • Replay mode: EMA smoothing is applied to the entire score series after computation
  • Live scoring: The previous smoothed score is stored and used as the EMA seed for the next cycle
  • Hysteresis: Applied after smoothing, using the previous recommendation as context

Signal Stability Metric

The validation metrics now include a Signal Stability percentage, measuring how often the recommendation remained unchanged between consecutive data points. Higher stability (>70%) indicates the smoothing and hysteresis are working effectively.

Limitations

  • EMA smoothing introduces a lag of approximately halfLife/2 periods in detecting true regime changes
  • The fixed hysteresis margin may be too aggressive for highly volatile instruments and too conservative for stable ones
  • In rapidly changing markets, smoothing may delay important signal transitions