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The first test conducted below explores the use of the time-reversed Slow %K network (developed when studying entries) as an additional element to our modified standard exit strategy The net, which generates what might be called a signal exit, cannot be used on its own for exiting because it will not always close out a trade This network was designed to provide entry signals When it generates a signal, the market is likely to behave in some expected manner However, the absence of a signal does not mean that the market will not do something significant When a position is being held, at some point an exit has to be taken, and that action cannot be postponed until a significant event is finally predicted The MSES, in this case, guarantees that all trades have some money management protection and are exited after a given amount of time.

Customers become more loyal if they look up what they need themselves. The costs to the supplier are lower than the costs of the traditional ordering system. You eliminate the customer service reps, the phone calls, and the manual typing of orders. Errors in ordering are reduced, since a well-designed Web site provides a picture of the product being ordered and the correct part number.

The neural net, however, can possibly improve the strategy by occasionally triggering an exit when a predicted move against the trade is expected In this way, the net may turn a certain proportion of losing trades into winners..

Let s start with what we know. Every company in America has put its inventories and its technical information on computers. This has happened in the last 20 years. These data are available to company employees using PCs or mainframe terminals. In most midsized or larger companies today, authorized employees can look up almost anything and see it on a computer screen. The next step may cost some money, but it is de nitely achievable. Get a programmer to make the data on the screens available to customers through the Web. Set up a microsite that major customers can access using a PIN and a password. Make the site user-friendly, following the three-click rule: Everything that anyone would want to see on the site should be available in three clicks of a mouse. To do this, you have to think like a customer: What would I, as a customer, want to see on this site Then design the site with that in mind. Work with your customers to design the site. Make getting information and ordering very easy. Set up their accounts so that they can get information free and parts or services, which they have to pay for, with one click (see Figure 11-3 for an example). Amazon is a master at this technique. Amazon lets its customers look up all their past purchases through the Web. I have bought so many books from Amazon that I sometimes cannot remember what I have bought. In three clicks, I can nd out all the books and videos that I have ever bought from Amazon, including the prices I paid and the dates I bought them.

The second batch of tests (one for the long side, one for the short) involves the use of a genetic algorithm to evolve a set of rules tcr generate a signal exit The rules are used in a manner similar to the way the net is used, ie, to generate additional exits, witbin the context of the MSES, when the market is likely to reverse The rule templates and rule-generating methodology are the same as those used in 12, where evolved rules generated entries In the current tests, rules are evolved to generate additional exits within the context of the MSES The rules are used as signal exits The additional exits will, it is hoped, improve profitability by turning some losses into wins and by killing other trades before they become larger losses More sophisticated exits can be developed using the techniques described above.

Data appending was rare and was done mainly by the largest companies Today, many companies add demographic data (age, income, presence of children, credit ratings, and scores of other facts) to their customer database routinely Business-to-business marketers add Dun & Bradstreet (D&B) data (SIC code, annual sales, number of employees) to all customer and prospect les These data are used for segmentation and crafting of marketing communications Customer segmentation was rare Few companies had identi ed their Gold customers, or knew what to do with them once they were identi ed Today many companies have segmented their customer base and have developed different marketing strategies for each segment Communication with customers was mostly by direct mail or telephone calls Phone calls cost several dollars each Letters were also expensive As a result, communications with customers were limited to monthly statements and sales calls.