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Table 5-l shows the portfolio performance of the close-only channel breakout system broken down by sample and market (SYM). (For information about the various markets and their symbols, see Table II-1 in the Introduction to Part II.) NETL = the total net profit on long trades, in thousands of dollars; NETS = the total net profit on short trades, in thousands of dollars; ROA% = annualized return-on-account; PROP = associated probability or statistical significance; AVTR = average protlt/loss per trade. Trend-following methods, such as breakouts, supposedly work well on the currencies. This test confirms that supposition: Positive returns were observed both in-sample and out-of-sample for several currencies. Many positive returns were also evidenced in both samples for members of the Oil complex, Coffee, and Lumber. The profitable performance of the stock indices (S&P 500 and NYFE) is probably due to the raging bull of the 1990s. About 10 trades were taken in each market every year, The percentage of wins was similar to that seen in Test I (about 40%). Test 3: Close-Only Channel Breakout with Entry on Limit on Next Bar, Transaction Costs Assumed. To improve model performance by controlling slippage and obtaining entries at more favorable prices, a limit order was used to enter the market the next day at a specified price or better. Believing that the market would retrace at least 50% of the breakout bar (cb) before moving on, the limit price (limprice) was set to the midpoint of that bar. Since most of the code remains unchanged, only significantly altered blocks are presented:

Acquiring customers by giving discounts. It works in the short term, but the customers do not stay with you. Assuming that every acquired customer is valuable. Many of them can be unpro table. Concentrating on acquisition to the exclusion of retention. Hanging on to customer names and not exchanging them with others.

Trade entry took place inside the bar on a limit. If inside-the-bar profit target and stop-loss orders were used, problems would have arisen. Posting multiple intrabar orders can lead to invalid simulations: The sequence in which such orders are tilled cannot be specified with end-of-day data, but they can still strongly affect the outcome. This is why the standard exit employs orders restricted to the close.

This chapter opens the door, so to speak, to my kitchen. The foods in my pantry and refrigerator contain the vitamins, minerals, and micronutrients intrinsic to the process of detoxification.

1. In the prospect penetration case study, what can you use the target potential index for a. Determining which customers are worthless b. Determining your retention budget c. Deciding which prospects you should aim at acquiring d. Nothing, since it is a worthless idea e. Scrap paper 2. What factor was not used to select prospects in the Key Equipment case a. Major industry b. Products purchased c. Number of employees d. Year company started e. Sales volume 3. In the SalesLogix case, which of the following was not listed as being a problem to begin with a. There were no e-marketing campaigns. b. The company lacked high-technology products. c. There was no lead-management system. d. Telemarketing was not integrated. e. The cost per lead was $500. 4. Which of the following was not one of the results of the SalesLogix case a. Lead volume grew to 9600 per quarter. b. Online events grew to 12 per month. c. Telemarketing was outsourced to a better bureau. d. The system ltered out 25 percent of raw leads. e. There was 100 percent lead tracking. 5. In the BMW study, which one of the following was not done a. Using Experian data in regressions. b. Delivering personalized content to prospects. c. Assigning LTV to each customer and participant. d. Using variables to score prospects. e. None of the above; all these things were done.

Performance Statistics for Close-Only Channel Breakout with Entry at Open for All Markets in the Standard Portfolio

6. List four product categories that cluster coding probably works for and four that it probably doesn t work for. 7. Which of the following is probably not true of most companies a. The company pays bonuses for customers, not for longterm customers. b. The company does not know whether new customers will be long-term or not. c. The company has not computed the LTV of customers or prospects. d. The company is highly customer-centric. e. Marketing and sales are going in different directions. 8. Why did the Weekly Standard custom approach work a. Customers are dumb. b. Customers like to have their views agreed with. c. It was a uke. Most such copy fails. d. The numbers are probably fake. e. None of the above. 9. In the timeshare case, if no-hook tours perform better, why does anyone sell hook tours a. The data are wrong. Hook tours are better. b. Hook tours are traditional. c. It takes time to change an established system. d. It is hard to persuade people that what they are doing is wrong. e. Answers b, c, and d. 10. What are three things that msdbm did for BMW that helped to solve the problem

As before, the look-back parameter was stepped from 5 to 100, in increments of 5, and the solution with the best risk-to-reward ratio (and t-test probability) was selected. Commissions, slippage, exit parameters, and the ability to reenter a continuing trend (albeit on a pullback), remain unchanged. With a best look-back of 80 (same as in Test l), this model returned about 33% annually during the in-sample period. The probability that these returns were. due to chance is less than 5% when not corrected, or 61% when corrected for 20 optimization runs. Although profitable in-sample, the statistics suggest the