Exponential moving average
An average in which the weight of an observation decays as it recedes into the past, so recent intervals count for more.
Formula
EMA_t = \alpha P_t + (1 - \alpha) EMA_{t-1}Alpha is the smoothing coefficient derived from the chosen period; P is the price of the interval.
How to read the number
It answers to fresh data faster than a simple average because old observations are not dropped all at once when they leave a window — they lose weight gradually.
When the metric lies
The quicker reaction is paid for in false turns of the line. The past never leaves the calculation entirely, so the lag never disappears either.
Also known as: ema