I could probably write an entire book about the numerous applications of moving averages.
I’m not focusing on how these technical indicators are calculated. I am assuming that most readers already know what a moving average is, or how an oscillator is derived. I provide an overview into the basics in this chapter, but for an in-depth explanation into the math, I highly recommend two books that are classics in the field: Technical Analysis of the Futures Market, by John J. Murphy (Paramus, NJ: New York Institute of Finance, 1999) and The New Commodity Trading Systems and Methods, by Perry J. Kaufman (New York: John Wiley & Sons, 1987).
I employ a set of specific moving averages, and I prefer exponential moving averages, rather than simple moving averages. An exponential raises the quantity of factors used by weighting the input toward the most recent price data, thus diminishing the weighting of the input from the back end of the time frame being averaged. The exponential moving average still captures the entire range of price action during its assigned time frame; it simply gives more importance to the more recent action.
According to Kaufman’s book, the technique of exponential smoothing was developed in World War II for tracking aircraft. By applying a geometric progression to a nearby weighted moving average, the U.S. military could project the future flight path of an airplane based on the trend of its movements and the short-term changes to such. ...