Section 2:

Objectively Identifying Trends Part II

 

Single Moving Average Method

Moving averages are the simplest and most effective technical indicator among the innumerable technical indicators that traders use today. Moving averages are used to objectively identify the collective actions of buyers and sellers and are, in fact, the most popular tool used to define trends.

Moving averages simply smooth a data series over a preset period of time. In doing so, moving averages help to remove some of the randomness associated with stock prices and help to consistently and objectively identify trends.

Moving averages come in many forms, the two most popular of which are simple and exponential. Simple moving averages look back over a defined period of time, such as 20 days, and average prices over the period. Exponential moving averages differ in that they give more weighting to the most recent periods over a defined period of time. This weighting makes the exponential moving averages more responsive to recent changes in the price of the stock. But there’s not a big difference between exponential and simple moving averages, especially over short periods such as 20 days.

The 20 day exponential and simple moving averages are displayed on the chart of DELL in Figure 2.4 . There’s an insignificant difference between the two.

Figure 2.4

There’s a significant difference between exponential and simple moving averages in longer time periods such as 200 days. Notice the gap between the two moving averages in the DELL example in Figure 2.5 .

Figure 2.5

An exponential moving average might be preferred over a simple moving average when trading longer time horizons. Over shorter time horizons, however, there’s very little difference.

The time horizon over which a simple or exponential moving average is applied will depend on a number of factors. Further discussion will follow throughout the tutorial. For now, consider some of the following time horizons and their significance.

5 day – 5 trading days in the week (short-term)
20 day – 20 trading days in the month (short-term)
50 day – Generally used by institutional traders (intermediate-term)
60 day – 60 trading days in the quarter (intermediate-term)
200 day – Generally used by institutional traders (long-term)
250 day – 250 trading days in the year (long-term)

No matter the type of moving average or the time period of the moving average, the rules for defining trends are the same:

The trend is bullish if today’s moving average value is greater than yesterday’s value.
The trend is bearish if today’s moving average value is less than yesterday’s value.

The moving average will continue rising so long as the stock is trending higher. This helps to identify and confirm existing trends. Looking at DELL in Figure 2.6 , the stock is steadily moving higher along with the 20 day moving average. The 20 day moving average is at $28.84.

Figure 2.6

The moving average is at $28.87 the next day, even though the stock moved measurably lower as shown in Figure 2.7 . This is the lag effect of the moving average coming into play. The trend is still bullish because the rule is still intact. But a change in trend might occur in the next day or two.

Figure 2.7

The trend changes to bullish the next day, after the stock drops substantially lower as shown in Figure 2.8 . The 20 day moving average falls to $28.84, less than the previous day’s reading of $28.87.

Figure 2.8

After the initial change in trend, when DELL was at $27.82, the stock continued to drop as shown in Figure 2.9 . Clearly the supply and demand dynamic shifted. The Single Moving Average Method forecasted a shift in trend, which was quite accurate in the following weeks.

Figure 2.9

A reversal from a bearish to a bullish trend starts when the 20 day moving average stops going lower. In the next example shown in Figure 2.10 you can see the 20 day moving average is still moving lower, currently at $22.65.

Figure 2.10

The stock moves substantially higher the next day, but the moving average actually drops by $0.01 to $22.64 as shown in Figure 2.11 . This example once again reveals the lag effect of the moving average.

Figure 2.11

The trend changes from bullish to bearish the next day in Figure 2.12 when the 20 day moving average jumps to $22.69, $0.04 higher than the previous day’s reading.

Figure 2.12

The Single Moving Average Method worked extremely well in the DELL examples above. That’s because DELL was trading within the context of a couple of steady trends. But not all trades work out so well. The flaw in the Single Moving Average Method is exposed when a stock’s volatility increases, but lacks an overall trend. Such an example is seen in Federal National Mortgage, or Fannie Mae, (FNM), in Figure 2.13 .

Figure 2.13

The stock whipped around its 20 day moving average for five months. Notice how many changes in trend occurred based on the Single Moving Average Method.

Single Moving Average Method Summary

Advantages:

Simple – A single moving average can identify trends.
Quick – A read of today’s and yesterday’s moving averages reveals the trend.
Consistent – Offers a very precise way of identifying trends.
Objective – It’s an either-or proposition most of the time.

Disadvantages:

Slow – Volatile moves in the stock could render the method ineffective.
Possibly Confusing –Today’s moving average value could equal yesterday’s.