V.9:6 (219-223): Building A Variable-Length Moving Average by George R. Arrington, Ph.D.
Product Description
Building A Variable-Length Moving Average
by George R. Arrington, Ph.D.
Of the tools in the technician's arsenal, the moving average is one of the most popular. It is used to eliminate minor fluctuations in prices, filter data noise and identify any underlying trend. Ideally, a moving average is sensitive enough to signal when a new trend has begun, yet able to ignore short-term random price movements at the same time.
As long as the underlying trend continues, longer averages work well, but shorter averages do a better job of indicating changes in trends. As a result, many technicians use two or more averages to identify emerging trends and to generate buy/sell signals.
In a variable-length moving average (VLMA), the length of the average depends on the relative magnitude of recent price changes. If recent price changes are "unusually" large, the length of the moving average is shortened and the average automatically becomes more sensitive to emerging trends. Conversely, if price changes are stable within a given narrow range, the length of the moving average automatically increases.
If the market is not trending, prices will tend to fluctuate around the arithmetic mean of the data series. A common measure of the degree of dispersion about the mean is the standard deviation. The likelihood of actually observing unusually high or low prices decreases as prices get farther away from the mean (that is, more standard deviations).
Of the tools in the technician's arsenal, the moving average is one of the most popular. It is used to eliminate minor fluctuations in prices, filter data noise and identify any underlying trend. Ideally, a moving average is sensitive enough to signal when a new trend has begun, yet able to ignore short-term random price movements at the same time.
As long as the underlying trend continues, longer averages work well, but shorter averages do a better job of indicating changes in trends. As a result, many technicians use two or more averages to identify emerging trends and to generate buy/sell signals.
In a variable-length moving average (VLMA), the length of the average depends on the relative magnitude of recent price changes. If recent price changes are "unusually" large, the length of the moving average is shortened and the average automatically becomes more sensitive to emerging trends. Conversely, if price changes are stable within a given narrow range, the length of the moving average automatically increases.
If the market is not trending, prices will tend to fluctuate around the arithmetic mean of the data series. A common measure of the degree of dispersion about the mean is the standard deviation. The likelihood of actually observing unusually high or low prices decreases as prices get farther away from the mean (that is, more standard deviations).
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