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Putting It All Together

Now that we’ve completed the parallel function and given a few examples of its operation on selected system inputs, lets put the indicator portion of the puzzle together in a form which will allow more thorough system testing.

The code below allows 3 inputs for all three critical variables of the system – delay, target and stop. The inputs allow the user to select a starting value for each variable from which the system analysis will begin. An incremental value can also be entered for each variable allowing the indicator to calculate 8 simulations for each variable.

By observing the individual plots for delay, target and stop the user now has a fairly good idea of which settings are going to be best for the optimal performance of the system, but up to now has not been able to observe the multiple system analysis across all inputs. With this next step, the user can enter a range of settings for each variable according to the observations from the previous indicator plots and then observe indicator readings representative of the total system using a varied range of variable inputs.

Input: Delay_Start(45),Delay_Inc(5),Tgt_Start(5),Tgt_Inc(1),Stp_Start(4), Stop_Inc(1);

Vars:   Pts(0), TTlPts(0);

Arrays:   BSys[8](0), BSysT[8](0);

BSys[1] = OMW_BO(Delay_Start + (Delay_Inc*0),Tgt_Start + (Tgt_Inc*0),Stp_Start + (Stop_Inc*0));

BSys[2] = OMW_BO(Delay_Start + (Delay_Inc*1),Tgt_Start + (Tgt_Inc*1),Stp_Start + (Stop_Inc*1));

BSys[3] = OMW_BO(Delay_Start + (Delay_Inc*2),Tgt_Start + (Tgt_Inc*2),Stp_Start + (Stop_Inc*2));

BSys[4] = OMW_BO(Delay_Start + (Delay_Inc*3),Tgt_Start + (Tgt_Inc*3),Stp_Start + (Stop_Inc*3));

BSys[5] = OMW_BO(Delay_Start + (Delay_Inc*4),Tgt_Start + (Tgt_Inc*4),Stp_Start + (Stop_Inc*4));

BSys[6] = OMW_BO(Delay_Start + (Delay_Inc*5),Tgt_Start + (Tgt_Inc*5),Stp_Start + (Stop_Inc*5));

BSys[7] = OMW_BO(Delay_Start + (Delay_Inc*6),Tgt_Start + (Tgt_Inc*6),Stp_Start + (Stop_Inc*6));

BSys[8] = OMW_BO(Delay_Start + (Delay_Inc*7),Tgt_Start + (Tgt_Inc*7),Stp_Start + (Stop_Inc*7));

If BSys[1] <> Bsys[1][1] then BSysT[1] = BSyst[1] + BSys[1];

If BSys[2] <> Bsys[2][1] then BSysT[2] = BSyst[2] + BSys[2];

If BSys[3] <> Bsys[3][1] then BSysT[3] = BSyst[3] + BSys[3];

If BSys[4] <> Bsys[4][1] then BSysT[4] = BSyst[4] + BSys[4];

If BSys[5] <> Bsys[5][1] then BSysT[5] = BSyst[5] + BSys[5];

If BSys[6] <> Bsys[6][1] then BSysT[6] = BSyst[6] + BSys[6];

If BSys[7] <> Bsys[7][1] then BSysT[7] = BSyst[7] + BSys[7];

If BSys[8] <> Bsys[8][1] then BSysT[8] = BSyst[8] + BSys[8];

Plot1(BSysT[1]*250,"Best1");

Plot2(BSysT[2]*250,"Best2");

Plot3(BSysT[3]*250,"Best3");

Plot4(BSysT[4]*250,"Best4");

{end;}

The chart above identifies the results of simulated testing across all three system variables, each with its own starting value and incremental values.

The box at right lists the results of each of our 8 system simulations as of the date at the top of the window. Each is color coded to one of the plots in the above chart.

By being aware of the inputs for the indicator, one can graphically determine which settings were optimal for the system at any one given time through the course of the chart.

For instance, on the date shown, 2-25-99, the magenta simulation, reflecting system settings of   75, 11 and 10 for delay, target and stop respectively, is showing the best overall net profit for the system with a net of $29,450 for the period beginning 1-5-99.

It is also obvious from the results presented that the system we have developed here meets our criteria of a robust system as the results of a wide array of variable settings produce a smooth progression of values. Note that there are no settings which greatly outdistance any of the others, assuring us that the system results are not the result of one system setting catching a huge trade which accounts for the majority of the profits for the system.