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The “Using Moving Averages In Commodities Trading" article examines and elaborates upon the benefits and advantages moving averages offer to investors in the commodities and futures markets and how to identify the signals generated in order to help individuals identify profitable trading signals.
Moving averages, or the arithmetic mean, are probably the most flexible and popular technical indicators used by investors today. Unlike most other indicators used in technical analysis, the results from using moving averages are easily quantifiable and serve as the foundation for most mechanical trend following systems. Since chart analysis is interpretive by nature, it is difficult, if not impossible to program it objectively into a computer. Moving averages, on the other hand, are easily computerized. Moving averages are the simple average of prices over a given time period. For example, a 20 day closing price moving average is the sum of the closing prices for the last 20 days divided by 20.
Trending, not predictive
Moving averages are trend following mechanisms. They are used to single the start of a new trend or the reversal of an old one. Unlike chart formations, they don't predict, but rather follow trends. Moving averages present the underlying trends in a market in a more easily understood view. The shorter the moving average, the closer it is to the actual price changes registered. Consequently, short term moving averages are more sensitive to actual price movements, while longer moving averages are far less sensitive. Studies have shown that optimum moving averages differ from market to market.
Reading moving averages
The basic principle behind the use of moving averages is that when a closing price moves above the moving average, this is a signal to buy. When the same price moves below the moving average, it is a signal to sell.
Some analysts also want to observe the slope of the moving average line in the same direction as the price crossing. The shorter the moving average, the more sensitive it is to price movements, and consequently, the more trade signals it will produce. If the moving average utilized is too sensitive, the investor risks receiving false signals because of random price movements. This produces a greater amount of trading with concomitant higher costs associated with that type of activity. Shorter moving averages may produce more false signals, but they have the advantage of catching trends earlier on.
Different moving averages work better in different types of market conditions. Shorter-term moving averages tend to work best in horizontal range trading markets. When markets are in a clearly definable longer-term trend, longer moving averages produce better results, as they do not get caught in minor corrections. On the other hand, the use of longer-term averages result in profit giveback because of the time delay necessary for a reversal signal. The longer moving average is ideal only as long as the market remains in a long term trend.
Filtering moving averages
Variations on the use of moving averages include the use of some sort of filter. Many investors will require not only that the moving average be surpassed, but that there is also a minimum movement above or below. The reason for this is to try to filter out false signals. One popular filter is to construct not only a moving average based on closing prices, but to also have parallel moving averages based on daily highs and lows. Buy and sell signals are only recognized if the appropriate upper or lower band is penetrated.
Another popular technique is the use of two different moving averages to generate signals. In this method, a shorter and a longer-term moving average have cross each other for an entry point to be identified. For example, in this method if one were using five and 20 day moving averages, a sell signal occurs when the five day moving average breaks the 20 day moving average below, whereas a buy signal happens when the five day average crosses above.
Moving averages are time-tested proven indicators that produce profitable results for any investor in the commodities and futures markets. Optimal performance using moving averages results when the analyst can identify the type of market that exists, and then subsequently use the appropriate moving average as an indicator.
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