If you recall in my article centred on technical analysis, I mentioned that there are an array of indicators and other methods that analysts use pertaining to the discipline. One of these frequently used indicators is called an ‘exponential moving average’ and this article will explain what it is.
What exactly is it?
‘Exponential moving average’ (EMA) is a specific type of moving average (MA) that places a greater weight (a description of adjustments that are made to a figure in order to reflect a variety of proportions or ‘weights’ of components that collectively make up that figure) and significance on the most recent data points. It is additionally a point of reference as the exponentially weighted moving average. An exponentially weighted moving average reacts more noticeably to the most recent price changes than a simple moving average (SMA). Those apply an equal weight to all of the observations within the period.
A moving average is defined as being a widely used indicator in the technical analysis discipline. It assists in smoothing out price action by way of filtering out the “noise” from randomly generated short-term price fluctuations. It is a trend-following (otherwise known as ‘lagging’) indicator due to the fact that it is based on past prices. The most common uses of moving averages are mainly to identify the trend direction. In addition, they determine the levels of support and resistance.
Much like all moving averages, EMA is a technical indicator that produces buy and sell signals based on crossovers and divergences from the historical average. Moreover, traders frequently use several different EMA days. For instance, 20-day, 30-day, 90-day, and 200-day moving averages.
The formula for the exponential moving average is the following:
There are three basic steps to calculating the EMA. They are:
- Calculate the SMA
- Compute the multiplier for the smoothing (or weighting) factor for the previous EMA
- Calculate the current EMA
How to calculate it
In order to properly calculate an EMA, the first thing you do is compute the simple moving average over a specific period of time. The calculation for the SMA is pretty straightforward. It is merely the sum of the stock’s closing prices for the number of time periods in question. Then one divides it by that exact same number of periods. For example, an SMA that goes for 20 days is simply the sum of the final closing prices for the past 20 trading days, divided by 20.
For the next step, you must calculate the multiplier for smoothing (weighting) the EMA, which will usually follow this formula:
[2 ÷ (selected time period + 1)]
With that in mind, for a 20-day moving average, the multiplier would end up being:
[2/(20 + 1)] = 0.0952
Finally, in order to calculate the current EMA, the following formula needs to be used:
[Closing price – EMA (previous day)] x multiplier + EMA (previous day)
The EMA will give a higher weighting to the most recent prices, while the SMA appoints equal weighting to all values. The weighting that is given to the most recent price is greater for a shorter period EMA than it would be for a longer period EMA. For example, a multiplier at 18.8% is applied to the most recent price data for an EMA of 10 periods, whereas for a 20-period EMA, only a 9.52% multiplier weighting is employed. In addition, there are some slight variations of the EMA that arrive by utilizing the open, high, low or median price as opposed to using the closing price.
What does it tell you
When it comes to the short-term averages that people commonly quote and/or analyze, the 12 and 26-day exponential moving averages are arguably the more popular of the bunch that is prone to examination. The 12 and 26-day are common mechanisms that create indicators that are akin to the moving average convergence divergence (MACD) and the percentage price oscillator (PPO). For the most part, the 50 and 200-day EMAs are signals of long-term trends. Whenever a stock price crosses its moving average of 200 days, it is a technical indicator that a reversal (a change in the general price direction of an asset) has taken place.
Traders who frequently employ technical analysis often find moving averages to be incredibly useful and insightful. However, this is only when they apply them correctly. Having said that, they can create havoc when used in an improper manner or are misinterpreted. All of the moving averages that are common in technical analyses are, by their very nature, ‘lagging indicators.’ These are a measurable economic factor that consistently transforms. However, that is only after the economy has begun to follow a specific type of pattern or trend. Moreover, it trails the price action of an underlying asset. Traders usually employ it as a means to generate transaction signals or confirm the strength of a given trend.
As a result, the conclusions drawn from applying a moving average to a particular market chart should be to validate a market move or to indicate its overall strength. Most of the time, as soon as a moving average indicator line has made an alteration to reflect a significant move in the market, the optimal point of market entry has already passed.
Due to the EMA computation placing more weight on the latest data, it “hugs” the price action comparatively tighter. Therefore, it reacts more quickly. This is a desirable quality whenever an EMA is a tool that derives a trading entry signal.
From here, we transition into explaining how one goes about interpreting the EMA.
Much like all moving average indicators, EMAs are much better suited for trending markets. Whenever the market is in a strong and maintained uptrend, the EMA indicator line will also present an uptrend. Plus vice versa for a downtrend.
A trader that is very attentive will pay close attention to the direction of the EMA line. Not only that, but they will also watch the relation of the ‘rate of change’ from one bar to the next. For instance, as the price action belonging to a strong uptrend begins to flatten and reverse, the EMA’s rate of change from one bar to the next bar will start to dwindle until such a time in which the indicator line flattens and the rate of change is zero.
Because of the prominent lagging effect at this point – or a few bars before – the price action should’ve already reversed. It follows, so observing a consistent decline in the rate of change of the EMA could itself be an indicator. It could further aid in countering the dilemma caused largely by the lagging effect of moving averages.
Common uses of exponential moving averages include conjunction with other indicators to confirm any significant market moves and to measure their validity. For traders who primarily trade intraday (meaning “within the day”) and fast-moving markets, the EMA is more applicable. Most of the time, traders will use EMAs as a means to determine a trading bias. For example, if an EMA existing on a daily chart shows a strong upward trend, an intraday trader’s strategy would probably be to trade only from the long side on an intraday chart.
SMA: what’s the difference?
The description of a conventional simple moving average is it is an arithmetic moving average that is the result of a computation by way of adding recent closing prices and then dividing that by the number of time periods in the calculation average. Investopedia editor, Adam Hayes, explains that:
“A simple, or arithmetic, moving average that is calculated by adding the closing price of the security for a number of time periods and then dividing this total by that same number of periods. Short-term averages respond quickly to changes in the price of the underlying, while long-term averages are slow to react.”
At this point, it seems like an appropriate time to discuss what sets EMAs apart from simple moving averages. Going just by their names, they may appear very similar, however, there is one major difference between the two and that is the sensitivity each one displays towards changes in the data that the system incorporates in its calculation.
To be more specific, the EMA gives a higher weighting to recent prices. The SMA, on the other hand, assigns equal weighting to all values. The two averages do share a similarity in that many interpret them in a similar manner. They are popular tools for technical traders to use in order to smooth out price fluctuations. Because EMAs place a higher weighting on recent data than older data, they are more reactive to the latest price changes than SMAs are. This, in turn, makes the results from EMAs more convenient. It also explains why the EMA is the preferred average among numerous traders.
The limitations of the EMA boil down to the uncertainty as to whether or not more emphasis should be placed on the most recent days within the time period or on data that is more distant. A number of traders believe that new data will effectively reflect the current trend that the security is moving with. Meanwhile, there are others who feel that privileging certain dates than others will create biases within the trend. Thus, the EMA is subject to recency bias.
Likewise, the EMA relies wholly on historical data. A lot of people, including economists, are of the belief that markets are efficient; that is to say, current market prices already reflect all of the available information. If markets are efficient, using historical data shouldn’t tell us anything about the future direction of the assets’ price.
EMA an indicator that is a popular tool for technical analysis, and for good reason: it has a solid reputation. Given the complexity of how it functions and what it conveys, it’s difficult not to see its appeal.