From the November 01, 2009 issue of Futures Magazine • Subscribe!

Using price shocks to time the market

At any given time, the price of a real commodity (such as the meats or grains) depends upon numerous independent variables. Cocoa prices are a product of the weather in Africa, the cost of shipping, government policies, the availability of substitute crops, pests, consumption levels, etc. Essentially, all of the various factors can be grouped as those affecting supply or those affecting demand. In normal times, price remains relatively stable as the supply and demand factors cause price equilibrium.

Periodically, an extremely unusual and unexpected event will occur. A hurricane or brutal freeze hits Florida, wiping out the orange juice crop. A war in Kuwait cripples the supply of oil. Prices soar. Swine flu hits Mexico, causing demand for hogs to irrationally evaporate. Prices drop dramatically.

If you’re on the right side of these shocks, you can profit immensely. Hog futures crashed from a high of 88.975¢ per lb. on Aug. 8, 2008, to 53.90¢ on Nov. 5, 2008. This is a 35¢ plunge in less than 90 days — a loss of 39% of value, or roughly 1% every two days. One contract of lean hogs is 40,000 pounds; hence, every penny price change represents a gain or loss of $400. A speculator who went short at the high and covered at the low would have earned $14,030 gross, or about $160 per day. Given the extremely low initial margin for hogs, this is an astronomical annualized return and something traders dream about.

Of course, it is easy to discern these points in hindsight. Wishing to know about them in advance causes us to fantasize about crystal balls. As technical traders, we try every possible method to find the philosopher’s stone, that mystical key to unlock the secrets of future price action. However, all of our neat statistical tools have little basis as determinants of future price activity.

A statistic, such as a moving average, is nothing more than a mathematical transformation of data points. A five-day moving average is just a method of representing five data points in a single number. A regression line is the line that best fits historical data; it reduces the total squared distance from each point to the line. There is no magic about it. Statisticians and technicians believe price will continue to fall in some reasonable range around the regression line. However, statisticians will caution you that such belief only holds over a short time period and assumes no fundamental underlying changes in the
independent variables.

That is the key. We know that life does include fundamental changes in variables. Traders see this all the time. Yet, prices of the real commodities eventually deal with the outrageous event. After some period of reaction to the price, the factors of supply and demand inevitably resume their inexorable forward motion and price eventually returns to stability.

Looking at the data in “Extreme hogs” the average price is 59.17¢. The net change totals 423.48 gross points, or an average swing of 38.5 points between peaks and valleys in an average of 13 months. However, the averages do us little good, and the data demonstrate the difficulty with cycles based upon fixed time or fixed price.

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