INDICATORS
A Closer Look At A Classic
Examining The EMA
by Tim Treloar
You know how to apply the exponential moving average, but what do you know about its development and behavior? Here's a deeper look at the popular moving average.The popular exponential moving average (EMA) depends on data to develop its distinctive characteristics, and when it comes to data, more is better. But before you put an EMA to work as a technical indicator, a deeper understanding of its development and behavior is advised. At the very least, a deeper understanding will justify the practical application of it and at most dispel some misconceptions associated with it.
IN THEORY
An EMA is essentially a type of weighted average. The idea of a weighted average is simple: each element in a collection of numerical data is multiplied by a number ranging from zero to 1 (the decimal equivalent of the percentile range zero to 100), called a weight, such that the sum of the weights always totals 1, and the weighted elements are then added together.
A simple moving average (MA) is perhaps the simplest example of a weighted average in that all the elements receive exactly the same weight. In an exponential moving average, the weight of each element decreases progressively, usually according to its age and usually by powers of a particular factor. This is done under the premise that recent data is more relevant than older data. The smaller this factor, the faster data devalues, heavily favoring the most recent data -- in other words, a short-term EMA. The larger the factor, the slower data devalues, distributing favor more equitably over a longer range of data -- a long-term EMA. At some point, the value of old data becomes so small that it can be effectively negligible.
Because the sum of the weights in a collection of data always totals 1, weight must be drawn in some manner from among the other weighted elements in order to make wight available for new additional data. Where in the collection of elements this weight is drawn from has a pronounced effect on the short-term evolution of the weight distribution, but in the long run the weight distribution of all EMAs that use the same parameters will become virtually identical. When represented graphically with bars, the characteristic profile of an EMA weight distribution is a stepped, gradually tapering curve, like steps descending into the base of an escalator.
...Continued in the June issue of Technical Analysis of STOCKS & COMMODITIES
Excerpted from an article originally published in the June 2008 issue of Technical Analysis of
STOCKS & COMMODITIES magazine. All rights reserved. © Copyright 2008, Technical Analysis, Inc.
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