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It must be determined whether the stock is being accumulated or is being distributed If it is not clear, then it is sometimes best to exit the stock than to take a chance that it is being distributed and will eventually move against you and go down and cost you money Give the stock a little time to show itself in these situations, but waste no time in closing out an inconclusive stock and moving on to another trading situation Livermore often sold a stock that had even moved a point or two in his favor, but he simply did not like the weak or limp manner in which it was acting It did not matter to him even if he had a small pro t or a small loss the major fact remained the stock did not do what he had analyzed and believed that it would do.

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So the conclusion was obvious and always simple to him his judgment had been wrong and therefore he must exit the trade One thing he knew for sure was that his judgment had been wrong in the past and that it would be wrong again in the future The danger was in not recognizing his mistakes and getting out in time The old adage is correct pride often does come before a fall The worse kinds of stocks are what he called Listless Drifters These are stocks that do not move in the desired manner and simply tie up a stock market trader s capital as they hang out there drifting in no man s land Whenever Livermore was forced to depend on hope, he always felt exposed to danger.

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When he simply took his loss, he knew what it was, and he know what he would have to make back to get into pro t Also, if he stayed with the losing or listless position, it had a negative psychological effect and always bothered him as he moved ahead with future trades Livermore discovered that he could not afford to trade in anything but live stocks, stocks that are leading the pack, stocks that have inherent energy This energy, or momentum, always meant trading on both sides of the market the upside and the downside, long or short..

varies across individuals When the accumulated effect of visits becomes high relative to this threshold, purchase occurs 4 Evolving effects over time The expected magnitudes of both visit effects and purchasing threshold may evolve over time, as the customer gains experience with the shopping environment For example, subsequent visits to a Web site may have smaller effects on purchasing as the shopper gets used to the environmental stimuli and becomes less persuaded by content that has been seen repeatedly in the past Therefore, our Conversion Model will allow for and provide a measure to characterize the trends that may be affected by past visiting Additionally, purchasing thresholds may also evolve as a function of past purchasing experiences For example, as shoppers make repeated purchases, the original reluctance to purchase from an unknown site may decrease, making future purchasing more likely.

Many researchers have found that customers are less resistant to purchase from a particular store in the future if they have already purchased from them in the past The paper immediately dives down into some serious math the type that reminds me why I was an English major, specializing in Shakespeare Needless to say, that math is there to validate the conversion model and compare it to several others If you were not a Shakespeare major, you might like to download the whole paper from wwwmarketingwhartonedu/people/faculty/faderhtml It's all a matter of applying the right numbers to the right situation If you run a portal, like Excite, your perspective is different Kris Carpenter tells me they apply this type of data in a couple of ways: The first is in understanding what sort of feature sets to prioritize, and it varies by application.

This program repetitively uses recursive procedure Fp providing top-down navigation of the hierarchy with bottom-up acknowledgment of actions in nodes (rule none its bracketed option simpli es the distributed control, allowing us to avoid the use of rule sequence). For example, we can create a three-layer hierarchy shown in Figure 6.3, where an additional layer to the two-layer hierarchy in Figure 6.2 has two local heads: head1 and head2 (subordinate to global head), and each local head has two subordinate group members. The program creating this hierarchy (also supplying certain initial coordinates to the nodes) will be as follows:

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