A moving average chart is used to assess the stability of a process. It is used in various fields, including construction and manufacturing, for analyzing minor movements and variations in processes over a specific time period. Moving average control charts are an essential technical tool for most stock and commodities traders who utilize them for identifying market trends and reversals. Traders also rely on these charts to determine an asset’s support and resistance zones, and to set stop-losses. The two most common methods for creating chart moving averages are the simple moving average method and the exponential moving average method.
Variable data, such as cost, time, and price, are used to compute the points that will be plotted on the moving average chart. The simple moving average method calculates the mean, or the average of a set of data points. This can be demonstrated in stock and commodities trading by using a series of closing prices to create a 30-day simple moving averages chart.
Closing prices over the last 30 trading days are added together and divided by 30. The resulting answer is then plotted on the moving average chart. The next point entered on the moving average control chart is computed by dropping the oldest closing price and adding the most recent data. When the data plotted on the chart is connected, a smoothing curve begins to form. The first day on this particular simple moving average chart starts on the thirtieth day.
The simple moving average is known as a lagging indicator, because prices follows behind the trend. Traders tend to rely on this technical tool only when market prices are trending in an established direction, up or down. Simple moving averages are not as reliable in markets that are moving sideways. Some traders compensate for this weakness by creating moving average charts using the exponential moving average method.
The exponential moving average chart will display movement that is closer to the direction of the prevailing trend. This is possible because the formula for calculating an exponential moving average, which is more complex, gives added weight to the newer price, or the most recent variable. By assigning additional weight on the recent price, the exponential moving average chart will display data that demonstrates a more accurate response to price change when compared to a simple moving average chart. Since the weighting is determined by the time-frame used for computing the chart, less weight is applied for longer periods and vice versa. For the 30-day average moving chart, the weight assessed to the latest price may be 7.52%, compared to a weighting of 18.75% for a 10-day moving average chart.