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1. (a) Personalized catalogs 2. (a) It provides no sales lift. 3. To reach high end customers; to reduce ordering costs; to open up another channel 4. They spent 33 percent more than regular customers. 5. Cross sales were up 100 percent. 6. They need to add: a. Customer pro les capturing emails and customer preferences and demographics. This reaches 20 percent on the rst round and an additional 20 percent on each additional round. b. One-click ordering for all customers completing their pro le, plus personalized emails and Web site opening pages.

A superior exit should be able to hold a trade for as long as it takes to capture a significant chunk of any large move; ie, it should be capable of riding a sizable move to its conclusion However, riding a sizable move to conclusion is not a critical issue if the exit strategy is combined with an entry formula that allows for reentry into sustained trends and other substantial market movements In reality, it is almost impossible, and certainly unwise, to discuss entries and exits independently To back-test a trading system, both entries and exits must be present so that complete round-turns will occur If the market is entered, but never exited, how can any completed trades to evaluate be obtained An entry method and an exit method are required before a testable system can exist.

However, it would be very useful to study a variety of entry strategies and make some assessment regarding how each performs independent of the exits Likewise, it would be advantageous to examine exits, testing different techniques, without having to deal with entries as well In general, it is best to manipulate a minimum number of entities at a time, and measure the effects of those manipulations, while either ignoring or holding everything else constant Is this not the very essence of the scientific, experimental method that has achieved so much in other fields But how can such isolation and control be achieved, allowing entries and exits to be separately, and scientifically, studied.

We will assume a modest CRM warehouse containing data on 14 million prospects and past customers and 6 million current customers. Let us assume that we can build it for $10 million, including the software

All the tests that follow were performed using oscillator entries to trade a diversified portfolio of commodities, Can oscillator entry models result in profitable trades How have they fared over time-have they become more or less profitable in recent years These questions will be addressed below. The exits are the standard ones, used throughout this book in the study of entry models. Entry rules are discussed along with the model code and under the individual tests. Trades were closed out either when an entry in the opposing direction took place or when the standard exit closed the trade, whichever came first. The test platform is also standard. Over the years, we have coded into C+ + the various oscillators described in articles from Technical Analysis of Stocks and Commodities and from other sources. When writing this chapter, we compared the output from our C+ + implementations of the classic MACD, Stochastic, and RSI oscillators with (when available) equivalent oscillators in TradeStation. In most cases, there was perfect agreement of the results. However, for one of the Stochastics, the results were extremely different, specifically for Slow %K. Examining the code revealed that TradeStation was computing Slow %K by taking an exponential moving average of Fast %K. Our code, however, computes the 3-bar simple moving averages of both the numerator and the denominator (from which Fast %K would have been computed) to obtain Slow %K. According to the equations in Meibahr s (1992) article, and in other sources we have encountered over the years, our C+ + implementation is the correct one. If the reader attempts to replicate some of our work in TradeStation and finds discrepancies, we strongly suggest checking the indicator functions of TradeStation. In addition,

for access, with annual maintenance costs of $1.5 million, which include the costs for the staff, NCOA (National Change of Address), and appended external data. Amortized over 3 years, the warehouse will cost us $5.5 million per year, as shown in Table 2-1. Let s compare this to the cost of database marketing in the same situation, shown in Table 2-2. It costs far less. We are assuming a cost of $1.5 million to build the database. Many databases are built for far less, such as $500,000, and some, of course, cost more. The number $1.5 million is a good number for a large corporate marketing database.