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Table 14-l shows the annualized risk-to-reward ratio (ARRR), the percentage of winning trades (WIN%), and the average trade profit or loss (AVTR), for every combination of money management stop and profit target limit parameter settings At the right of the table, the AVG or average values (average taken over all money management stop parameters) for all the performance figures are presented for each profit target limit parameter value At the bottom of the table, the AVG or averages (taken over all profit target limit parameters) for each of the money management stops are shown A number of things are immediately apparent in the results As the profit target limit got tighter, the percentage of winning trades increased; this was expected A tight profit target has a greater chance of being hit and of pulling a small profit out of the market.

Weldon U.S. customers universe Metal production Light manufacturing Heavy manufacturing High technology Total 254 15,442 44 612 29,198 2,433 162,009 1,288 1,453 167,183 Penetration ratio 10.44% 9.53% 3.42% 42.12% 17.46% Lifetime value $145,067 $5,914 $988,145 $127,675 Target potential $15,144.68 $563.70 $33,756.51 $53,776.39 Rank 3 4 2 1

However, the increased percentage of winning trades with tighter profit targets was not sufficient to overcome the effects of cutting profits short on trades that had the potential to yield greater profits Looser profit targets performed better than tight ones For most of the profit target limits, there was an optimal placement for the money management stop, between a value of 10 and 20 average true range units away from the entry price As the stop got looser, the percentage of winning trades increased, but the other performance figures worsened As it got tighter, the percentage of winning trades declined along with the other measures of performance The overall optimal performance, in terms of both annualized risk-to-reward ratio and average trade, was with a profit target limit of 45 and a money management stop of 15.

Target potential is derived by simply multiplying the penetration ratio by the lifetime value. This is a simple approach, but it has value. Here is another approach to customer acquisition for a business-tobusiness situation.

As deviation from the optimal combination occurred, the annualized risk-to-reward ratio increased, as did the average loss per trade There was relatively little interaction between placement of the profit target and the money management stop The values that were optimal for one varied only slightly as the parameter controlling the other was adjusted Another almost equally good combination of parameters was 15 and 4 (profit target and stop, respectively) This provided a very slightly better average trade and a trivially worse annualized riskto-reward ratio It is interesting that the arbitrarily assigned values came fairly close to the optimal values, appearing only one cell away from the optimal cells in Table 14-l The optimal values, however, provided 6% more winning trades than the arbitrary values of 4 (profit target) and 1 (stop)..

Equipment nancing is not really like any other type of business The amounts involved can be huge The terms, the length of the lease, and the items nanced are seldom standard (as they are in automobile or home mortgage nancing) It is hard to predict companies need for nancing, as decisions on equipment purchases are seldom made on a predictable schedule As a result, nding leads is tough Which companies are going to need nancing, and when The situation is complicated by the fact that the industry is highly competitive In addition to banks, there are nance companies that specialize in equipment nancing There is very little customer loyalty, as decisions are made primarily on rates rather than on provider af nity, service, or brand To further complicate the picture, the equipment nancing sales force, like all sales forces, is highly skeptical of central assistance.