Smoothing
Averaging recent data to reduce short-term noise and reveal an underlying trend.
Smoothing is the general technique of averaging recent data points to reduce short-term noise, making an underlying trend or pattern easier to see. Nearly every moving average and oscillator applies some form of smoothing to raw price or volume data before plotting it.
Different smoothing methods make different trade-offs between responsiveness and noise reduction. A simple moving average smooths by weighting every period equally; an exponential moving average smooths by weighting recent periods more heavily; Wilder's smoothing (used inside RSI, ATR, and ADX) uses yet another weighting scheme. None eliminates lag entirely — more smoothing generally means less noise but a slower reaction to genuine change.
Examples
- A 20-period simple moving average smooths price by averaging the last 20 closes equally.
- RSI's average-gain and average-loss calculations use a specific smoothing method (Wilder's) rather than a plain average.