Among the different metrics and indicators used in trading, the so-called “moving averages” are widely used as tools to show some basic trends in the evolution of the price of an asset. For that reason, traders should familiarize themselves with them in order to get the most out of them when creating their buying and selling strategies.
At a theoretical level, moving average can be defined as a trend following technical indicator which is based on past data to provide an average value. For example: in a 10-day moving average, a daily value on the curve corresponds to the average price that the asset has had in the last 10 days.
Thus, each day the new daily value of the moving average is generated with the calculation of the corresponding average. Since a simple average of the values of the selected period is used, this average is also called a simple moving average (SMA).
The first effect of calculating day by day the averages of a given period is that sudden price movements are attenuated, because an average value is being taken each time. The following graph shows the 10-day moving average of the price of bitcoin, which, although it is very close to the price quoted in the market, offers a version of it in which the volatility of the market is attenuated.
It can be assumed that moving averages of short periods, less than 20 days, eliminate noise or sudden price changes. In this sense, a trader can see what is the price that is consolidating in a market and create strategies based on these indicators.
Knowing, in general terms, what moving averages are and roughly what they are used for, then we are going to delve into how traders can use this tool to monitor and evaluate market behavior.
As we have mentioned before, the simple moving average is calculated using the simple average of the values of a specific period of days. However, there are other types of averages, also known as weighted averages, which give more weight to the most recent values of that period. That is, to the last days of the metric. To do this, a series of coefficients are selected that are larger for recent values than for older values.
Thus, as can be seen in the graph, the 10-day weighted average (10D WMA) follows the main curve more closely than the simple moving average (10D MA). Thus, the weighted moving average is preferred over the simple moving average not only because it reflects faster trend changes.
Furthermore, its usefulness is reflected in the fact that minimizes the effect of unusually low or high values that can occur punctually in a price curve. A trader can follow these indicators to spot any movement in the market that could reverse or consolidate the rise or fall in price.
exponential moving average
Another tool crypto traders have is the exponential moving average (EMA). This, in general, is a type of weighted moving average, in which the assigned coefficients decrease according to an exponential curvethus the EMA reflects changes in the price of an asset more quickly than the simple moving average.
The chart below shows the 20-day simple moving average (20D MA) in blue, as well as the 20-day exponential moving average (20D EMA) in red. Note the fact that the EMA reflects trend changes sooner than the simple moving average.
On the bitcoin peso daily candlestick chart, both curves are descending. Nevertheless, it is found that the EMA (red) reacts first than the simple average or MA (blue) to changes in trend, reflected in the last three daily candles in red. In other words, it is one of the fastest tools to capture possible indicators of change in a trend.
The fact that the exponential average is above the moving average in the last three days, indicates that the EMA is taking into account the slight price increases that occurred in previous days.
These price increases, being relatively small, do not change the trajectory of the simple moving average. However, in the case of the EMA it could be giving a signal that, despite the general downtrend continuing, there are indicators that could be associated with a change in trend. And, in this way, the trader will be warned that an opportunity may arise to enter or exit the market.
Moving average as an indicator of bitcoin price support
Moving averages based on an extended period, for example over 1,000 days, have been used as indicators of support for an asset price.
Specifically, the 200-week or 1,400-day exponential moving average (200W EMA), which takes data from approximately 4 years ago, has served traders as a guide to the evolution of the bitcoin price floor.
The chart below shows the price and the 200-week moving average. It can be seen that, in bearish times, this curve indicates the level of the minimum price of the cycle. It is noted, however, that there are specific areas in which the price crosses below the curve.
Bitcoin Price Cap Proposal
When the period of days associated with a moving average is extended, it no longer stays close to the price. In addition to moving away, it is moving downwards, with respect to the main curve. This is a logical consequence since when a sufficiently long period is taken, the prices of the past are lower and lower and the resulting average is lower.
We have already seen that the 200-week moving average can support the price of bitcoin. But there are cases where we speak of the moving average of larger periods, even reaching the extreme of a “perpetual” moving average curve. This moving average, proposed by Willy Woo, takes into account the prices of bitcoin from the earliest times in which that cryptocurrency began to be traded.
On Willy Woo’s website dedicated to graphing most important bitcoin metricsthis analyst proposes this average of extended moving average to calculate a curve that serves as an indicator of the maximum prices of bitcoin.
On the chart, the average curve, below the price curve and the price top curve are plotted. The latter comes from the lower average curve, multiplying by 35 each value of the lower curve. This empirical procedure achieves a “ceiling” for the price, so that previous all-time highs touch the top curve.as can be seen in the graph.
Moving average crossovers will be addressed in a future installment as a price predictive tool. For this, the interaction of two moving averages of different periods is analyzed, which can generate bullish or bearish indicators when they cross.