Read more about displaced moving averages on Investopedia. Install the modules The modules that we will be needing are listed below and you can simply install them with a pip3 install. This allows you to plot what are commonly referred to as "displaced" moving averages. 1 Photo by Ishant Mishra In this article, I will be showing you how you can calculate the Exponential Moving Average of a stock using Python. Moving averages have an Offset parameter that allows you to shift the average plot forward or backwards (negative offset value). In addition, you can choose what element of price to use in the calculation of the average: Last, Open, High, Low, or Typical Price. All three averages are plotted using a period of 30 simple (red), exponential (cyan) front-weighted (yellow). The formula for this indicator is quite simple: (close - MA)/MA The MA value is subtracted from the close in order to determine the difference between the two values. You can see how the different averaging types produce different results. A 5 period front weighted average is calculated as follows (C is the most recent bar, C4 is 4 bars ago):įront Weighted Average = ((C*5) + (C1*4) + (C2*3) + (C3*2) + C4) / 15 Next, you must calculate the multiplier for smoothing (weighting) the EMA, which typically follows the formula: 2 (number of observations + 1). It is calculated differently than exponential averages but it also gives recent data more weight. For example, a 20-day SMA is just the sum of the closing prices for the past 20 trading days, divided by 20. The weighting for each older data point decreases exponentially, giving much more importance to recent observations while still not discarding older observations entirelyĪ front-weighted average, like an exponential average, allows the most recent data being averaged to impact the average value more than older data. The good news is that the SMMA indicator is available by default on most trading platforms. Because it is a combination of both the EMA and the SMA, the formula for calculating the smoothed moving average might come off a bit complex. If the period is 3 and the last three data points are 3, 4 and 5 the most recent average value would be (3+4+5)/3=4 (divide by three because there are three data points).Īn exponential moving average (EMA), sometimes also called an exponentially weighted moving average (EWMA), applies weighting factors which decrease exponentially. Microsoft Corp stock chart Source: Calculating the Smoothed Moving Average. offers three different types of moving averages.Ī simple moving average gives equal weight to each data point for the period. Moving averages are used to smooth trends. Usually calculated to identify the trend direction of a stock or to determine its support & resistance levels.
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