Tips on Technicals - Moving Averages
Although stock and commodity prices follow trends higher and lower, they can be quite volatile. For example, the long term trend in stocks for the last decade has been up but medium and short term trends, such as the extreme events of October 1987, can move in exactly the opposite direction. To smooth out this volatility, the moving average is used.
Simple Moving Averages
There are several types of moving averages currently in use today. The most basic is the simple moving average which takes the prices from the previous user-defined number of periods, sums them up and divides by the number of periods. A 10 day average is simply the average closing price for the past 10 days. Each successive day is calculated fresh from the 10 most recent days. This is how the average "moves". The number of periods to use in the average depends on the stock or commodity being analyzed. Typically, it is related to the cycle of the underlying item, such as a four year stock market cycle, seasonal heating oil cycle and an agricultural harvest cycle.
The average is overlaid on the price chart and crossovers between the average and the underlying price are observed. When prices are rising they are usually above the average. This is to be expected since the average includes data from the previous, lower priced days. As long as prices remain above the average there is strength in the market. Buyers are willing to pay more for the stock or commodity as the market continues to value it higher.
When prices cross below the average it means that the market no longer expects prices to continue higher, at least temporarily. The more market participants taking this new view, the higher the volume will be and the better the signal. Remember, the valuation in the market is based on what market participants think will happen in the future. If the price is expected to rise, buyers will buy it now at the lower price which in turn causes demand to rise. Rising demand means higher prices and the self-fulfilling prophesy will been sustained.
Figure 1
Figure 1 is a 200 day line chart of Merrill Lynch. The 21 day average being used is typical for a large US stock and provided support for the summer 1993 rally. Since an average smoothes out volatility, it serves as a proxy for the trend itself so when prices crossed below the average in early October, a warning was given that the stock would reverse. When the average itself turned lower in mid October, the signal was confirmed. Note that prices crossed the average several times without the stock reversing. None of these false signals were confirmed by other indicators such as RSI or volume.
Weighted and Exponential Averages
Moving averages are lagging indicators. They summarize previous data and plot it on current prices so an analyst using only moving averages will probably not be able to call tops and bottoms in the markets. He will see the change in the trend only after it has happened. The potential profit lost by the inability to pick tops and bottoms is offset by the reduction in volatility seen and the reduced risk of making a bad trade.
In order to reduce the lag of the simple average, we can assign more weight to recent data and less to older data. A weighted 10 day moving average assigns a weight of 1 to the first day, 2 to the second and so forth until the most current day which is assigned a weight of 10. The 10 weighted values are added together and the sum is divided by the sum of the weights, which in this case is 55.
Exponential averages are similar to weighted averages in that they give more importance to recent data. The difference is in how it assigns the weights. It is not important for this discussion to go into details of the formula except to say that a weighted average is an arithmetic weighting, and exponential average is a geometric weighting. This really only means that it reacts even faster to price changes than the other averages.
Figures 2 and 3
Moving Average Envelopes
Some markets react differently in bull and bear markets. For these, it is useful to base moving averages on high and low prices instead of closing prices. For example, to confirm a new bull market the analyst might require prices to cross above the moving average of the highs. This adds additional filtering of volatility without having to use longer, and less sensitive, averages.
This leads us to moving average envelopes which are simply a pair of moving averages above and below price (sometimes envelopes are referred to as trading bands). Figure 2 shows May 1993 CBT Soybeans with 50 day high and 50 day low simple averages. Breakouts higher are indicated by prices crossing above the high average. Conversely, new market declines are indicated by crosses below the bottom low average. Note how crossovers below the top average in March 1993 were not confirmed by crosses below the bottom average. This envelope did not signal "sell" but lead to higher profits as the rally resumed.
Envelopes are also created by taking a moving average of the close and adding and subtracting a certain percentage of the average value. Figure 3 shows March 1993 NYMEX Crude Oil for one year. The envelope shown is a 2½% band centered on a 14 day moving average. The moving average selected served as a good proxy for the short term trends for Crude Oil that year and the two and one half percent value is a commonly used parameter across markets. By selecting the envelope parameters to contain the normal volatility of the market, the analyst can determine if overbought or oversold conditions are reached when prices move out of the envelope's borders. The analysis can be made more sensitive by decreasing the envelope width and less sensitive by increasing it.
Bollinger Bands® are envelopes defined by standard deviations instead of percentage from the average. The analysis is more complex so we'll save this discussion for another edition (Bollinger Bands®) of "Tips."
