EMA: Exponential Moving Average
This page contains information about the EMA pricing methodology.
The EMA (Exponential Moving Average) filter is a filter that can be applied to a time series of existing price points. These price points originate from one of the other filter methods (e.g., VWAPIR, MAIR, or MEDIR). The EMA filter then produces a moving average over a number of the latest of these price points.

Filter Application

The EMA filter is used as a post-processing filter in our graphql frontend. It uses the underlying MA120 filter points and produces a time series using a moving window approach.
For each EMA filter point, the algorithm takes into account a configurable amount of MA120 filter points from the past and calculated a weighted average. This weighting depends on the age of the MA120 filter points and decreases exponentially towards the past. By that the EMA filter ensures that recent data points have a higher weight in the filter end result compared to older ones.
A detailed writeup of EMA functionality can be found here.

Implementation

The filter is implemented as part of the FiltersBlockService in this file in our Github repository.
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Filter Application
Implementation