The exponential moving average (EMA) is a recursive average that updates by blending today's close into yesterday's EMA via a smoothing factor α = 2 / (N + 1). Older observations decay exponentially rather than dropping off a fixed window, so the EMA reacts faster to new price action than the equivalent-length SMA.
EMAs are the building block for many other indicators: MACD is the difference of two EMAs, the signal line is an EMA of MACD, and many strategies use a 9 / 21 / 50 EMA stack to gauge short- vs. medium-term trend.
The trade-off versus SMA: faster response in trending markets, but more whipsaws in chop. The smoothing factor α is unitless — the same EMA(20) on 1-minute bars and on daily bars uses the same recursion.
Formula
EMA_t = α · P_t + (1 - α) · EMA_{t-1}, where α = 2 / (N + 1)Example
For N = 10, α = 2 / 11 ≈ 0.1818. If yesterday's EMA was 100 and today's close is 110, today's EMA = 0.1818 · 110 + 0.8182 · 100 ≈ 101.82.
How Noon Barbari uses Exponential moving average (EMA)
Every concept here is implemented in the platform. Open the relevant docs or tool to see it in action.
See the indicators reference →Related terms
- Indicators
Simple moving average (SMA)
Unweighted arithmetic mean of the last N closes. Every bar counts equally.
- Indicators
Moving average
A rolling average of price over a fixed window, used to smooth noise.
- Indicators
MACD
Trend-momentum hybrid: difference of two EMAs, plus a signal-line EMA and histogram.
- Market structure
Trend
A persistent directional drift in price — up, down, or sideways.