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Fuzzy Logic in Stock Market Analysis

Traditional sorts of mathematical analysis generally yield hard yes or no answers. A number is, say, greater than 7 or it is not. There is another type of commonly asked question, however, which cannot readily be answered in this way. Suppose, for example, we wish to ask whether a given number is "a lot" less than 7, or "a lot" more, or is "rather close" to 7? Such questions cannot be properly answered by a simple yes or no. Suppose that we say that 6 and 8 are close to 7. Does that mean, however, that 5.9 and 8.1 are no longer "close" to 7? Intuitively, we may sense that this is not what we intend, but the conventional mathematics of set theory, and computer programs applying such mathematics, compel us to set such artificial boundaries.

Yet in a great many practical situations, however, we are not looking for yes or no answers, or seeking to define absolute boundaries, but are looking for characteristics that are less sharpely defined. Stock market analysis is one area in which we frequently encounter such situations. We can give an exact yes or no answer to some questions, such as whether a given stock is outperforming its industry group's average, or whether a given company's price/earnings ratio is above or below average for its group. But the stock analyst is seldom content with such a simple division of stocks into sheep or goats. He or she may want to ask questions with less distinct answers; is a stock "a lot" above or "a lot" below its group average?

Traditionally, a stock picker had no formal way to answer such questions, and was forced to fall back on intuition. A common method of proceeding might be to derive a whole series of specific yes-or-no answers, according to various measures, and then to weigh them. But the weighting process is itself intuitive. Particularly at a time when computer trading technology has made movements more sudden and volatile, the analyst would like to have some way of a...

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Fuzzy Logic in Stock Market Analysis. (1969, December 31). In LotsofEssays.com. Retrieved 10:45, March 28, 2024, from https://www.lotsofessays.com/viewpaper/1690480.html