In Pinescript, a smoothing technique applied to the standard moving average (SMA) creates a less reactive indicator known as the Smoothed Moving Average. This calculation involves averaging a series of moving averages, effectively reducing the impact of short-term price fluctuations and highlighting the underlying trend. For example, a 10-period smoothed moving average might be calculated by taking the average of the last ten 10-period SMAs. This double-averaging process filters out more noise, producing a smoother curve compared to a simple moving average.
Reduced noise and lag are among the key advantages of using this method. While a simple moving average can be prone to whipsaws and false signals due to price volatility, a smoothed equivalent provides a more stable representation of price action. This enhanced stability allows traders to identify trends more clearly and make more informed decisions. Historically, smoothing techniques have been employed to interpret various data sets, not just financial markets, aiding in forecasting and trend analysis across different fields.
