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stpprice = max(stpprice, Lowesf(lo,Z,cb)); break; case 2: stppcice = max(stpprice, cls[cbl -stpa*atr); break; case 3: trap = tbiicbl atpa * at=) - stpprice; if(tmp > 0.0) stpprice += stpb l tmp; break; case 4: mp = ChiIcbl sepa * atrl sfpprice; if(tmp > 0.0) stpprice += stpb * tmp; limprice = limprice - ptga'(limprice-cls[cbl); break; ) ts.exiflonglimit('F', limprice); ts.exitlongstopC'G', stpprice); if(cb-entrybar >= maxhold) ts.exitlongclose('E'l; 1 else if(ts.positionO < 0) ( // shorts ewitch(modeltype) ( case 1: stpprice = min(stpprice, Highesf(hi,P,cb)); break; case 2: stpprice = min(stpprice, cls[cbl+stpa*atr); break;

They are not smoke and mirrors, but projections of real events that will actually occur and can be veri ed Database marketing, therefore, becomes a combination of science and art The art, of course, is thinking up the strategies that will produce the improved customer relationships, and hence the improved repurchase rate The science is putting all these projections together in an LTV chart that makes sense and proves the value of your efforts..

s t p p r i c e ) ; maxhold) ts.exitshortclose( H );

To compute lifetime value, you need a customer database that includes transactions. You need to be able to estimate the revenue and the costs in order to compute the pro t from each transaction. You use past history to determine the retention (or repurchase) rate.

The code fragment above shows the implementation of the shrinking limit, along with the MEMA stop reported in Table 14-4. Table 14-5 provides information on the portfolio performance as the initial profit target limit @lim in the code, INIT in the table) and the shrinkage coefficient @&a in the code, COEFF in the table) are varied. The parameter that controlled the initial placement of the profit target, in average tree range units away from the price, was stepped from 2 to 6 in increments of 0.5. The shrinkage coefficient was stepped from 0.05 to 0.4 in increments of 0.05. The best combination of parameters produced a solution that was an improvement over the fixed profit target limit. The risk-to-reward ratio became - 1.32, the percentage of winning trades remained the same at 37%, but the average loss per trades was less at $1,325. Again, the model was well behaved with respect to variations in the parameters. The results indicate that care has to be taken with profit targets: They tend to prematurely close trades that have large profit potential. As can be seen in Table 14-5, as the initial profit target placement became tighter and tighter, the percentage of winning trades dramatically increased, as more and more trades hit the profit target and were closed out with a small profit. On the down side, the risk-to-reward ratio and the average worsened, demonstrating that the increased percentage of winning trades could not compensate for the curtailment of profits that resulted from the tight profit target. Sometimes it is better to have no profit target at all than to have an excessively tight one. The same was tme for the shrinkage rate. Profit targets that too quickly moved into the market tended to close trades early, thereby cutting profits short.

Lifetime value can at rst be computed for all customers as a group, but once it has been developed, it should be determined for customer segments. The LTV of an individual customer is derived from the LTV of the segment that includes that customer, adjusted for the products the customer owns and other factors that seem to determine the customer s particular LTV. Lifetime value produces numbers that can eventually be audited after the fact. A year later, you can go back and see what the retention (repurchase) rate was; what the spending rate was; what the marketing expenditures, the pro ts, and the discount rate were. It is not smoke and mirrors.

In all the tests conducted so far, a position was held for only a maximum of 10 days. Any position that still existed-that had not previously been closed out by

Computing LTV using complex formulas that your top management does not understand. If your management doesn t understand exactly how you developed it, it will have no con dence in it and will not use it pro tably. Looking at LTV numbers by themselves. An LTV number by itself is meaningless. Its most important use is in calculating whether proposed marketing programs will increase or decrease lifetime value. Spending resources on getting an exact lifetime value number. LTV is a future number. The future has so many unknown factors that you should use LTV as a rough guide: Do this, and don t do that. That is all it is good for.

Portfolio Performance as a Function of the initial Profit Target Limit Placement and the Shrinkage Coefficient

Fats essential, 52 55 polyunsaturated, 53 saturated, 52, 141 trans-fats, 52, 141 Fatty acids, 53 Fennel quinoa with roasted fennel, 183 Fermentation, 44 45 Ferulates, 51 Fiander, Dr., 101