Moving averages are one of the oldest and most
popular technical analysis tools. This chapter describes the basic
calculation and interpretation of moving averages. Full details on
moving averages are provided in Part Two.
A moving average is the average price of a security
at a given time. When calculating a moving average, you specify the time
span to calculate the average price (e.g., 25 days).
A "simple" moving average is calculated by adding
the security's prices for the most recent "n" time periods and then
dividing by "n." For example, adding the closing prices of a security
for most recent 25 days and then dividing by 25. The result is the
security's average price over the last 25 days. This calculation is done
for each period in the chart.
Note that a moving average cannot be calculated
until you have "n" time periods of data. For example, you cannot display
a 25-day moving average until the 25th day in a chart.
Figure 23 shows a 25-day simple moving average of
the closing price of Caterpillar.
Figure 23
Since the moving average in this chart is the
average price of the security over the last 25 days, it represents the
consensus of investor expectations over the last 25 days. If the
security's price is above its moving average, it means that investor's
current expectations (i.e., the current price) are higher than their
average expectations over the last 25 days, and that investors are
becoming increasingly bullish on the security. Conversely, if today's
price is below its moving average, it shows that current expectations
are below average expectations over the last 25 days.
The classic interpretation of a moving average is to
use it to observe changes in prices. Investors typically buy when a
security's price rises above its moving average and sell when the price
falls below its moving average.
Time periods in moving averages
"Buy" arrows were drawn on the chart in Figure 24
when Aflac's price rose above its 200-day moving average; "sell" arrows
were drawn when Aflac's price fell below its 200-day moving average. (To
simplify the chart, I did not label the brief periods where Aflac
crossed its moving average for only a few days.)
Figure 24
Long-term trends are often isolated using a 200-day
moving average. You can also use computer software to automatically
determine the optimum number of time periods. Ignoring commissions,
higher profits are usually found using shorter moving averages.
Merits
The merit of this type of moving average system
(i.e., buying and selling when prices penetrate their moving average) is
that you will always be on the "right" side of the market--prices cannot
rise very much without the price rising above its average price. The
disadvantage is that you will always buy and sell late. If the trend
doesn't last for a significant period of time, typically twice the
length of the moving average, you'll lose money. This is illustrated in
Figure 25.
Figure 25
Traders' remorse
Moving averages often demonstrate traders' remorse.
As shown in Figure 26, it is very common for a security to penetrate its
long-term moving average, and then return to its average before
continuing on its way.
Figure 26
You can also use moving averages to smooth erratic
data. The charts in Figure 27 show the 13 year history of the number of
stocks making new highs (upper chart) and a 10-week moving average of
this value (lower chart). Note how the moving average makes it easier to
view the true trend of the data.