When talking about weighted moving average in Forex markets, the most important distinction which can be made is the one between linearly weighted moving average and exponential moving average. Both types can be technically classified as weighted moving average, although it would be ill-advised to use them interchangeably, as this can result in massive losses for any Forex trader. Yes, both tend to assign higher values to recent data, unlike simple moving average which treats all data equally, but it only takes one look at their graphs to see the difference in their values. The linearly weighted moving average is a straight line, while the exponential moving average is a curve. Let’s see why:
SMA is not perfect
Over the time, the SMA has shown two critical flaws. One is not discriminating between the old data and the new, and the other was its limited time frame. Its shortcomings might have been overlooked if it weren’t for their (often) outlandish results. Not only would the SMA tend to “shorten” the amount of signal compared to the length of the window, but sometimes it would actually invert it, resulting in huge peaks created by the troughs in the data, and it also failed to remove some higher frequencies. The initial response came in the form of linearly weighted moving average, but it soon came to be eclipsed by the exponential moving average. The thing is, both of them assign more weight to recent data, and use improved calculation methods, resulting in far more smooth outcomes which are easier to follow and more reliable to boot.
LWMA (Linear Weighted Moving Average) vs EMA
When LWMA is applied, the weight added to entries decreases in arithmetic progression, right down to zero. With EMA, however, zero is never reached at all! This is because in EMA, the weighting factors decrease exponentially. The mathematical formulas are different. The mathematical formula for the LWMA involves multiplying values of each day with its number (the price on the 15th day is multiplied by 15, the price on the 16th day is multiplied by 16 etc.), adding them up and dividing it by the sum of the number of days (1+2+3+…n, where n is the last day in the time period). This is where things get confusing for many Forex and Bitcoin traders: they experience difficulties when distinguishing between WMA and EMA.
While the EMS does employ a similar weighting method (it is a ‘weighted’ average, after all) it also accounts for all the data in the life of the currency pair in its calculation. There is no actual beginning or a definite end, per se. Furthermore, it enables much more discretion when it comes to assigning weight to recent data, before adding it to the previous data for a total of 100%. For example, if you assign 15% weight to the last day’s data, the previous data are weighted at 85%. Yes, it will influence the result, but will never be enough to overshadow the remaining 85%.