Chasing The Trend With Moving Averages

Both these aspects form the basis of technical analysis. Robert Edwards and John Magee correctly stated that prices move in trends. To recognize the type of trend and the prevailing price momentum in every market scenario, it's always necessary to follow particular techniques like trend indicators, momentum oscillators, moving averages of different terms, and more.

In his book On Market Momentum, analyst Martin Pring analyzed various momentum-based indicators along with moving averages and their interpretation in the existing market. As he noted in his work Technical Analysis On Stock Market Trends: "The moving average is a fascinating tool, and it has real value in showing the trend of an irregular series of figures (like a fluctuating market), more clearly."

As the time span of the moving average gets longer, it tends to become smoother. Shorter moving averages will be more sensitive. So a five-day moving average will be more sensitive than a 10-day one. Besides applying them to stock prices to identify the market trends, moving averages can be applied to trading volumes.

Different types of moving averages:

Simple moving average (SMA): When calculating SMA, the data of the entire range is given equal importance. The averages are calculated by adding the closing price of the security for a specific period and dividing the sum by number of periods. For example, a 10-day SMA will be calculated as C1+C2+....C10)/10. On the 11th day, the closing price of the first day of the original series will be dropped and the moving average will be calculated as (C2+C3+....C11)/10. The simple moving average is also known as the arithmetic moving average.

Exponential moving average (EMA): When calculating the EMA, more weight is given to the recent data. Because of this it is considered to be more reliable, although more complicated to calculate, than the SMA. The EMA can be calculated based on percentage or number of periods. When calculating on a percentage base, a specific percentage is applied to the day's EMA. This percentage is calculated using the number of periods used to calculate the average.

Weighted moving average (WMA): When calculating WMA, the most recent data is given more importance. The method to calculate is lengthy but to give you an idea, the data for each day is multiplied by a weighted factor depending upon the number of days (period) in the average.

Triangular moving average (TMA): This moving average offers maximum weight to the middle values than the most recent or earlier data. The calculation of TMA yields curves known as the double-smoothed simple moving average. You can think of the TMA as the SMA of SMA.

Variable moving average (VMA): The VMA differs from all these moving averages. Here the emphasis is on volatility in recent data. If prices are volatile, a higher weight is applied to recent data. This tool is most useful in highly volatile markets. It adjusts its weight according to the market conditions.

Volume-adjusted moving average (VAMA): Richard Arms, developer of the Arms index and Equivolume charting, developed VAMA. Here, volume is the most important variable and more weight is placed on those days that had higher volume.

Among the six, the SMA and EMA are the most commonly used moving averages. By now you must have understood the importance of time span in moving averages. While interpreting moving averages, you can plot one short-term MA, say 10 or 20-day, one medium-term MA, say 50 days, and a long-term one such as the 200-day MA.

The crossover feature forms the basis for trend deviation and the moving average convergence/divergence (MACD) indicator. It is so named because two moving averages constantly converge and diverge with each other. MAs are exponential, the default parameters being the exponential moving averages of 12, 25, and nine days. The MACD oscillator can be combined with the SMA or EMA on a price chart.

Martin Pring finds that using moving averages as an indicator in isolation is more reliable than moving average crossover of raw oscillators due to numerous whipsaw signals, noting that "moving average direction change offers a promising approach for providing reliable and timely signals for momentum-trend reversal." In certain cases, trendlines can be constructed joining peaks or troughs on moving averages. When these lines are violated, more significant trade signals occur. The more the trendline gets tested by moving averages, the greater the strength of the trendline. But if the tool fails to give reliable signals, then that means you either have to expand the time period or smooth the average with an additional exponent.

Besides crossovers, moving averages also act as support and resistance levels. Support and resistance hold great value and generate buy or sell signals.

In an uptrend, the following price/moving average correlations generate buy positions when the price:

There is the possibility of whipsaws occurring if the price declines far below the MA line, and you can expect a short-term rebound.

In a downtrend, sell signals are generated in the following conditions when the price:

The penetration of the MA line will occur in close conjunction with the penetration of a trendline. The direction of the trendline and the moving average line will determine whether it will be a buy or sell signal. Moving averages can also be used to identify market consolidations or sideways movements.

There are more trading signals that can occur while you are trading. In my next Working Money article, I will discuss a few of the other indicators that are frequently used to identify trading signals.