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Test of the MEMA Dynamic Stop There are three parameters in this model: the initial money management stop pxameter, which sets the stop for the first bar; the ATR offset parameter (ATRO in Table 14-4); and the correction or adaptation rate coefficient (COEFF), which determines the relative rate at which the stop pulls in to the market or, equivalently, the speed of the modi@ed exponential moving average underlying this model. All three parameters are optimized with an extensive search. Table 14-4 shows portfolio performance only as a function of the ATR offset and the adaptation rate coefficient, the most important parameters of the model. The initial stop parameter was fixed at 2.5, which was the parameter value of the optimal solution.

percent. That means that out of every dollar you spend there, the store gets only a penny in pro t. A Web supermarket has to operate in that environment. It has to take that penny and use it to pack customers orders in boxes (using either low-cost workers or high-cost technology), put the boxes in refrigerated trucks, and deliver them to houses scattered all over a metropolitan area. No one can make any money doing that, and no one did. The Web supermarkets had to charge more than bricks-and-mortar supermarkets, but even the extra charge did not pay for the service they were providing. Furthermore, most Web supermarkets failed to achieve the pro ts from the impulse buying that takes over when people visit a real supermarket. No one goes to a supermarket to buy a quart of milk and comes home with just a quart of milk. But if you are ordering on the Web, you haven t made the investment to get into your car and drive to a supermarket, park, nd a cart, wander down the aisles, and then wait in line at the checkout counter. Everyone wants to make that investment worthwhile, so people pick up a few more items while they are there. A buyer on the Web who needs only a quart of milk doesn t see all the colorful vegetables piled up at the entrance. She doesn t see the ladies handing out samples to eat. She doesn t see the magazines at the checkout line. Her only investment is the $10 delivery charge. To avoid that delivery charge, she decides to pick up the milk at the 7-11 on her way home from work.

Portfolio Performance as a Function of First-Bar and LaterBar Stop Parameters Using the Dynamic ATR-Based StopLoss Model

Again, the model responded in a well-behaved manner to changes in the parameter values. There was some interaction between parameter values. This was expected because the faster the moving average (or adaptation rate), the greater the average true range offset must be to keep the stop a reasonable distance from the prices and achieve good performance. The best overall portfolio performance (the boldfaced results in Table 14-4) occurred with an ATR offset of 1 and an adaptation rate coefficient of 0.3 (about a 5-bar EMA). Finally, here is a stop that performed better than those tested previously. The risk-to-reward ratio rose (- 1.36), as did the percentage of winning trades (37%) and the average trade in dollars ( - $1,407). TEST OF THE PROFIT TARGET This test is the best stop thus far produced: The MEMA stop had an initial money management parameter of 2.5, an average true range offset of 1, and an adaptation

Consumers buy books, credit cards, travel, pornography, and nancial services on the Web. A much smaller number of people than had been anticipated in the 1990s look at or respond to ads. What they often do is research. Ordinary households use the Web as a combination of Yellow Pages and Consumer Reports. They look up maps, cars, appliances, real estate, and interest rates, and they use this information when they buy. Because of the Web, consumers are far better informed today than they were 5 years ago. It is not unusual to see a consumer going to a dealer carrying a PC printout that has all the background on what she plans to buy.

rate coefficient of 0.30. In the original MEMA test above (the results reported in Table 14-4), the optimal fixed profit target was used. In the current test, the optimal fixed profit target is replaced with a shn nking profit target, i.e., one that starts out far away from the market and then pulls in toward the market, becoming tighter over time. The intention is to try to pull profit out of languishing trades by exiting with a limit order on market noise, while not cutting profits short early in the course of favorably disposed trades. The approach used when constructing the shrinking