V.16:1 (33-37): Smoothing Techniques For More Accurate Signals by Tim Tillson

V.16:1 (33-37): Smoothing Techniques For More Accurate Signals by Tim Tillson
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Smoothing Techniques For More Accurate Signals by Tim Tillson

More sophisticated smoothing techniques can be used to determine market trend. Better trend recognition can lead to more accurate trading signals. Here's how.

After studying his first stock chart, the novice technician is most likely to learn next about moving averages. This is a reasonable progression. First, moving averages are easy to understand. The simple moving average is just the average of a given number, which we will refer to as n, of previous closing prices, recalculated each day at the close. And second, technicians use moving averages because the moving average offers a smoother visual image of the market trend. In effect, the moving average removes the noise around the trend. This concept of eliminating noise from the trend is similar to what engineers strive for in their application of digital filters. As R.W. Hamming observed:

Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done.

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