Exponential moving average

Objective

Exponential smoothing or exponential moving average is a rule of thumb technique for smoothing time series data using the exponential window function. Whereas in the simple moving average the past observations are weighted equally, exponential functions are used to assign exponentially decreasing weights over time.

Example

time window:
  emitting type: priceEMAAnalytics
  window functions:
  ema rates:
    function:
      exponential moving average:
        parameters:
          smoothing factor: 0.001996007984032
    attributes: [ ask,bid ]
  policy:
    type: slidingTime
    slide: 500
    window size: 2500

Output attributes

After processing, attributes receive automatically applied postfix ID = EMA

Before processing	After processing	Type
ask	ask_EMA	double value
bid	bid_EMA	double value

Parameters

Parameter	Description	Type
smoothing_factor	Smoothing constant to be applied within the EMA calculation Use ( 2 / 1 - Time Periods) as the smoothing constant.	Double Default: 0.333