SYSTEM DESIGN
IBM, Cubed
by Dennis Meyers, Ph.D.
Here's a look at whatÕs involved in developing a trend-following indicator for trading IBM.
In a previous article, I showed how the application of a curve generated by a third-degree polynomial could be used to develop a system to buy and sell British pound (BP) futures. This time, we will use a variation of that cubed system to create a system to trade IBM.
FIGURE 1: OPTIMUM PARAMETER VALUES FOR EACH WALK-FORWARD DATA SEGMENT. Here's a table of the three window data segments and their corresponding optimum parameter values. As can be seen, the cubic polynomial was picked as best in all three test windows, due to the ability of the cubic polynomial to model more complicated price wiggles than the quadratic polynomial.
IBM, one of the premier computer corporations in the world, is a major factor in the movement of the Dow Jones and Standard & Poor's 500 indices. Although IBM is traded on all regional exchanges, the lionÕs share and real market of IBM is traded on the New York Stock Exchange (NYSE).
DATA DISCUSSION
We will use the daily prices of Ibm from January 1, 1993, to December 31, 1998. IBM pays dividends on a quarterly basis, usually on the dividend payable dates of March 10, June 10, September 10, and December 10. On the ex-dividend date, the price of the stock is adjusted down by the value of the dividend. Thus, over the space of a year IBM has a small downward bias in price by the amount of the yearly dividend. If you were a holder of IBM, then you would receive those dividends in cash, and the small downward bias over the year would be made up by the cash dividends you received. However, in developing a system using IBM prices, those prices are not adjusted for the dividend payments. This nondividend adjustment creates a small distortion in parameter selection and walk-forward results, which should be noted but does not significantly affect the system.
THE LEAST-SQUARES QUADRATIC-CUBIC SYSTEM
In a previous article titled "Surfing The Linear Regression Curve," I used the least-squares technique to fit a straight line through 30-plus closing prices to create a curve that served as a proxy for the market trend. When the curve moved up by a certain percent from its previous low, the trend was assumed to have changed to the upside and a buy signal given. When the curve moved down by a certain percentage from its previous high, the trend was assumed to have changed to the downside and a sell signal given.
Dennis Meyers has a doctorate in applied mathematics in engineering. He is a member of the Chicago Board Options Exchange (CBOE), a private trader, and president of Meyers Analytics. His firm specializes in consulting for financial institutions and developing publicly available analytical software for traders. He can be reached 312 280-1687, via his Website at https://www.MeyersAnalytics.com, or via E-mail at meyersx@MeyersAnalytics.com.
Excerpted from an article originally published in the August 1999 issue of Technical Analysis of STOCKS & COMMODITIES magazine. All rights reserved. © Copyright 1999, Technical Analysis, Inc.
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