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Net profit and annual return were averaged for each market over all tests. The calculated numbers contained no surprises. Positive returns were seen in both samples for the Deutschemark, Swiss Franc, Japanese Yen, and Canadian Dollar, and for Light Crude and Heating Oil. Trading a basket of all six currencies, all three oils, or both, would have been profitable in both samples. Although no other market group demonstrated consistent profitability, some individual markets did. In order of minimum net profit, Coffee, Live Hogs, and Random Lumber had positive retarns. The S&P 500, NYFE, Comex Gold, Corn, and the wheats had positive outof-sample returns with in-sample losses. The index markets profitability may have resulted from the strong trends that developed out-of-sample. Positive insample returns, associated with out-of-sample losses, were somewhat more

Figure 14-8

common; T-Bonds, IO-Year Notes, Palladium, Feeder Cattle, Pork Bellies, Soybeans, Soybean Meal, Bean Oil, Oats, Orange Juice, and Cotton had this pattern. T-Bills, Silver, Platinum, Live Cattle, Cocoa, and Sugar lost in both samples. A correlation of 0.15 between net in-sample and net out-of-sample profits implies markets that traded well in the optimization period tended to trade well in the verification period.

performance of the responders. Use a control group to see if the nonresponders also do better. They will. Figure 14-8 shows the kind of information that the New York Times gets from its readers on the Web.

No technique, except restricting the model to the currencies, improved results enough to overcome transaction costs in the out-of-sample period. Of course, many techniques and combinations were not tested (e.g., the long-only restriction was tested only with the volatility breakout and not with the HHLL breakout, a better out-of-sample performer), although they might have been effective. In both samples, all models evidenced deterioration over time that cannot be attributed to overoptimization. Breakout models of the kind studied here no longer work, even though they once may have. This accords with the belief that there are fewer and fewer good trends to ride. Traders complain the markets are getting noisier and more countertrending, making it harder to succeed with trend-following methods. No wonder the countertrend limit entry works best! Overall, simple breakout models follow the aforementioned pattern and do not work very well in today s efficient markets. However, with the right combination of model, entry order, and markets, breakouts can yield at least moderate profits. There are many variations on breakout models, many trend filters beyond the ADX, and many additional ways to improve trend-following systems that have not been examined. Hopefully, however, we have provided you with a good overview of popular breakout techniques and a solid foundation on which to begin your own investigations.

One of the most innovative and practical methods of customer pro ling through Web response is the Web quiz. People are encouraged to go to a Web site to take a quiz. In most cases, the quiz concerns your product. When they take the quiz, they get a score that tells them whether they need your product and which of your products meets their needs. Iomega, the maker of Zip storage disks, turned to Bob McKim of msdbm of Los Angeles to design a Web quiz that would attract business customers. Msdbm has perfected this technique. The company used direct mail and email to prompt IT directors to come to Iomega s Web site to take a quiz (see Figure 14-9). The quiz asked the easy questions about data storage given in the following list. As you look through these questions and think about your answers, you will see that you are easily drawn into the Iomega way of thinking. Each question has a yes or no answer. 1. At least once a quarter we make copies of all our data and store them off site.

If possible, use a limit order to enter the market. The markets are noisy and usually give the patient trader an opportunity to enter at a better price; this is the single most important thing one can do to improve a system s profitability. Controlling transaction costs with limit orders can make a huge difference in the performance of a breakout model. Even an unsophisticated limit entry, such as the one used in the tests, can greatly improve trading results. A more sophisticated limit entry strategy could undoubtedly provide some very substantial benefits to this kind of trading system. . Focus on support and resistance, fundamental verities of technical analysis that are unlikely to be traded away. The highest-high/lowestlow breakout held up better in the tests than other models, even though