I enjoy reading books that others might consider outdated. Arthur Sklarew’s Techniques of a Professional Commodity Chart Analyst (Commodity Research Bureau, 1980) is a transitional book, written when “the click-buzz of computers almost drown[ed] out the shouting in the pits in Chicago and New York.” (p. xi) It covers some familiar ground—chart patterns, Elliott wave theory, trend lines, oscillators, and moving averages—all in support of trend trading. But there are twists even here; moreover, Sklarew offers some tools that are not commonplace.
Sklarew suggests that the commodity trader follow both the rule of multiple techniques (that is, the more technical indicators confirm each other the better the chance of an accurate forecast) and the principle of selective techniques. The former applies to chart analysis in general; the latter to automatic trading methods. “In very general terms, the Principle of Selective Techniques states simply that the automatic trading method that appears to work better than other methods in a particular market at a particular time is the one that should be used in that market at that time.” (p. 5)
Although Sklarew writes that “a chartist’s asset lies not so much in his being able to forecast how high or how low a market will go, or when it will get there, as in being able to identify the direction of a trend and to call the turn of a trend when it comes,” (p. 1) he offers a dozen methods for predicting how far a move will go. Here let me summarize one novel measurement technique. I haven’t tested it out, in part because I personally am not comfortable with measured targets. But a lot of people swear by them, so here is one of Sklarew’s contributions.
The rule of seven enables a trader to project one or more objectives in the direction of the new trend based on the initial leg of the trend. The formulas for uptrend and downtrend projections vary slightly. First, the uptrend formula: “Measure the size of the initial up-leg by subtracting the low price from the high; multiply that figure by seven; then divide that product by four to get the distance from the low to the first objective, divide the product by three for the second objective, and by two for the third objective.” In every case add the distance to the low. Or, in its simplified form: “Upside objective #1: High minus low, multiply by 1.75, add to low price. Upside objective #2: High minus low, multiply by 2.33, add to low price. Upside objective #3: High minus low, multiply by 3.50, add to low price.” In a downtrend, Sklarew writes, “the formula is moved back one notch. The three downside objectives are obtained by multiplying the size of the initial down-leg by 7/5, 7/4, and 7/3, or 1.40, 1.75, and 2.33 respectively, and subtracting the result from the high.” (p. 83)
Sklarew fleshes out the rule of seven, applying it to both minor and major trends, to trends of both large and small magnitude. Moreover, he suggests that in dynamic markets a fourth objective must be considered. In an uptrend, it is seven times the initial leg measured from the low of that leg; in a downtrend, it is 3.50 times the first leg projected downward from the high.
Sklarew also sets forth a 17-35 measurement. He admits that it is “difficult to find a logical reason why many sustained commodity futures price moves congest or reverse after covering a distance equal to 17% or 35% of the recent high or low price,” but he says that “this happens so frequently that it must be more than just a coincidence.” (p. 87)
This book offers tips from the former coffee and cocoa trader, mathematical formulas for many indicators, and backtested results from a study designed to find the best moving average for each of 13 commodity futures contracts. It may be thirty years old, but it offers fodder for today’s system testers.