First, we need to find the multiplier based on these two inputs. We would process it by using a smoothing factor of 2. The simple average of the first 50 data points would be the EMA t-1 in our first iteration since we do not have a history for the EMA. If we need to calculate the 50-day EMA, we would require 51 data points. Some of the parameters we need to define first are the smoothing factor and the number of days. Let us develop the EMA profile of an asset from scratch. The next section will tell you how to use the exponential moving average formula to calculate an actual EMA using different inputs, namely the closing price, smoothing factor, and the number of days. So, if you want to put more weight on the latest data point, you can do it by increasing the smoothing factor and decreasing the number of days. Multiplier = Smoothing Factor / (1 + number of days) The formula for the multiplier is the following: Here “t” denotes the instant for which the EMA needs to be calculated, and “t-1” is the previous instant. Price Action Trading Strategies That You Need to KnowĮMA t = Closing Price t * multiplier + EMA t-1 *(1 – multiplier).It is this particular feature that makes EMA a more effective tool than the simple average. A trader can customize the weight the indicator needs to assign to the latest data point based on their importance to the latest figure. On the other hand, the EMA would be more responsive to such changes by placing more weight on the latest developments in price. One would have to wait for a few days before it would actually reflect this information. A simple average indicator would not capture that momentum adequately. For example, if a company’s earnings result shows that it beat Street estimates, that may lead to a surge in price. ![]() In many cases, that’s not the most accurate figure. The disadvantage of a simple average is that it might not give you a number weighted too heavily on old data. This is different from calculating the simple average, where all data points have the same weight. By focusing more on the latest data points, the EMA ensures that the old and redundant data points do not have the same influence on the indicator as the latest data point. Exponential Moving Average or EMA is an advanced version of the simple average that weighs the most recent data points while calculating the average for a particular day.
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