Education Excerpt: Simple Moving AverageSimple Moving Average
The origin of inventing the Simple Moving Average (MA) is not clear. Although, some of the first documented cases of its use date as far back as the early 20th century. Implementation of moving averages in technical analysis is one of the most successful methods of identifying trends. Moving averages are simply constant period averages - usually of prices, that are calculated for each successive period interval. The result of calculation is then plotted on the chart as a smooth line that represents successive average prices. Thus, the calculation of the moving average dampens fluctuations of price of an asset, making it easier to spot an underlying trend. Though use of the moving average goes beyond identifying trends. Support, resistance and price extremes can be anticipated by correct interpretation of the moving average.
Crossover
Generally, when the moving average with a lower period interval crosses above the moving average with a higher period interval it is considered a bullish signal. On the other hand, when the moving average with a longer period interval crosses above the moving average with a lower period interval it is considered a bearish signal. These crossovers can serve as specific buy and sell signals in markets that are trending. However, moving average crossovers tend to produce many false signals in non-trending markets. Furthermore, these same crossovers can act as support or resistance levels.
Illustration 1.01
Picture above depicts daily graph of PepsiCo (Ticker:PEP) with 20-day SMA (blue) and 35-day SMA (red). With implementation of these two moving averages it is easily observable that prevailing trend is bullish. Crossovers between these two simple moving averages reveal where trend began (10th February 2017) and where it ended (7th July 2017). In addition to that analyst can identify price extremes when price deviates too far from its 20-day SMA.
Length of the period
Different lengths of moving average directly translate to the amount of data used in the calculation. Including more data in the calculation of the moving average makes each data per time interval relatively less important. Therefore, a large change in one particular data would not have as large an impact on the overall result of the calculation in comparison to if the moving average with a shorter period was employed. Hence, the longer moving average produces less false signals at the cost of revealing underlying trend sooner rather than later. Usually, the use of two moving averages with different period intervals is encouraged as opposed to use of a single moving average. This comes from the premise that when two moving averages with different period intervals are plotted on a chart, they tend to show two separate lines converging and diverging.
Illustration 1.02
Picture above depicts daily graph of XAUUSD with 3-day SMA (blue) and 6-day SMA (red). Viewer can see that 3-day SMA copies price move more agressively than 6-day SMA.
Illustration 1.03
Picture above depicts exactly same graph as is showed in Illustration 1.02. However, length of SMAs differs. Blue line represents 10-day SMA while red line represents 20-day SMA. It is clear that when length of SMAs was extended then SMAs produced less mechanical signals (crossovers) as opposed to SMAs used in Illustration 1.02.
Calculation
The calculation of the moving average usually involves use of the close price. Normally, 10, 20, 50, 100 or 200 periods are used and the calculation is conducted by creating the arithmetic mean of a dataset.
SMA = (A1 + A2 + An) : n
A = average in period n
n = number of time periods
Illustration 1.04
Picture above shows daily graph of Coca Cola (Ticker:KO). In this particular example trend was neutral and it is visible that crossovers between two simple averages produced many false signals.
Disclaimer: This content is just excerpt from full paper that will be published later. It serves educational purpose only.
