**Strategy Tester Report**

**N7S_AO_772012**

**Alpari-Demo (Build 220)**

Symbol | EURUSD (Euro vs US Dollar) | ||||

Period | 5 Minutes (M5) 2008.11.10 00:00 – 2008.12.19 22:59 (2008.11.10 – 2008.12.20) | ||||

Model | Open prices only (only for EAs that explicitly control bar opening) |
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Parameters | Trd_Up_X=true; tpx=5; slx=90; px=8; x1=44; x2=24; x3=78; x4=99; Trd_Dn_Y=true; tpy=5; sly=80; py=17; y1=2; y2=63; y3=31; y4=6; Text0=”BTS F=1″; F=1; pz=6; z1=31; z2=70; z3=27; z4=99; Text1=”BTS”; G=4; Text2=”XXXXXXXXXXXXX”; tpX=4.5; slX=20; pX=3; X1=8; X2=44; X3=40; X4=61; Text3=”YYYYYYYYYYYYY”; tpY=1; slY=80; pY=29; Y1=6; Y2=36; Y3=73; Y4=33; Text4=”ZZZZZZZZZZZZ”; pZ=31; Z1=56; Z2=71; Z3=45; Z4=93; | ||||

Bars in test |
9557 | Ticks modelled |
18110 | Modelling quality |
n/a |

Missmathced charts errors |
0 | ||||

Initial deposit |
2000.00 | ||||

Total net profit |
797.06 | Gross profit |
931.43 | Gross loss |
-134.38 |

Profit factor |
6.93 | Expected payoff |
15.63 | ||

Absolute drawdown |
2.20 | Maximum drawdown |
66.40 (2.39%) | Relative drawdown |
2.39% (66.40) |

Total trades |
51 | Short positions (won %) | 22 (81.82%) | Long positions (won %) | 29 (68.97%) |

Profit trades (% of total) | 38 (74.51%) | Loss trades (% of total) | 13 (25.49%) | ||

Largest | profit trade |
170.08 | loss trade |
-18.40 | |

Average | profit trade | 24.51 | loss trade | -10.34 | |

Maximum | consecutive wins (profit in money) | 7 (317.36) | consecutive losses (loss in money) | 2 (-8.80) | |

Maximum | consecutive profit (count of wins) | 317.36 (7) | consecutive loss (count of losses) | -18.40 (1) | |

Average | consecutive wins | 3 | consecutive losses | 1 |

Currency pair : different ones are possible, but only EURUSD has passed the full checking.

Chart period : М1, М5, М15. I use М5.

The testing and optimization can be performed by the open prices on M5. Some unessential differences in the results of testing on different timeframes are possible because of some peculiarities of the EA.

The algorithm of tuning (optimization) by two ranges with the two-level three-stage optimization is used in the EA.

The first range is set up with G=0 (not equal to 2,3,4)

First level F=0

First stage Trd_Up_X=true Trd_Dn_Y=false for the parameters with “x”

Second stage Trd_Up_X=false Trd_Dn_Y=true for the parameters with “y”

Second level F=1

Third stage Trd_Up_X=true Trd_Dn_Y=true for the parameters with “z”

The second range is less than the first one, it is tuned after it with G equal to 2,3,4

First stage G=2 for the parameters with “X”

Second stage G=3 for the parameters with “Y”

Third stage G=4 for the parameters with “Z”

The flags of states should have the following status after the full optimization:

Trd_Up_X=true Trd_Dn_Y=true F=1 G=4

The parameters of the х1..y2..Y3..Z4 type are optimized according to the NN rules, i.e. within the range from 0 to 100 (two-times value of the shift parameter in perceptron (50)). You can change it to 100 common value then the range will be from 0 to 200.

The slx sly slX slY parameters – initial stop is optimized from 20+ to 100+ depending on the wish and the abilities of the system.

The tpx tpy tpX tpY parameters – the coefficient for the corresponding SL level – usually from 2 to 5+ with the step equal to 0.2-0.5.

The “empiring” is still necessary to determine what ranges to use for the tuning, this is the hard and long process so I suggest all desirous ones to take part. I’ve been running two variants on the demo. First variant – the first range is 4-6 weeks with the weekly re-optimization, second range – 3-5 days with the re-optimization each 1-3 days.

Second variant – doesn’t have distinct parameters yet, I still experiment.