Cheetah (由 christof)
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Cheetah討論
Dec 01, 2009 at 06:25
會員從Nov 23, 2009開始
7帖子
November 2009 Additional Statistics
Number of trades = 907. (616 winners, 291 loosers, 83 absolute direction changes)
Average winning trade = 220 pips * 0.017 lots. (5 digit pips)
Average loosing trade = 220 pips * 0.018 lots.
Profit Factor = Gross Profit / Gross Loss = 2263 / 1105 = 2.05.
Net Profit / Total Spread = 1159 / (15 pips * 15.88 lots) = 4.86.
Number of trades = 907. (616 winners, 291 loosers, 83 absolute direction changes)
Average winning trade = 220 pips * 0.017 lots. (5 digit pips)
Average loosing trade = 220 pips * 0.018 lots.
Profit Factor = Gross Profit / Gross Loss = 2263 / 1105 = 2.05.
Net Profit / Total Spread = 1159 / (15 pips * 15.88 lots) = 4.86.
Dec 01, 2009 at 07:16
會員從Nov 23, 2009開始
7帖子
I cannot describe the system (there is none) or the specifics, but I can tell how it works in general:
The decision making is done by neural nets. Before november everything was done in mql4, and now everything is c++ (huge speedup). What I do is programming the input data, architecture, optimization algorithm, fitness function, etc. Then my pc does the number crunching. The results of each optimization run (several hours to days on my 3Ghz Core2Duo) are often pretty different, so I decided to combine some of them again, to yield a single number for market exposure.
The decision making is done by neural nets. Before november everything was done in mql4, and now everything is c++ (huge speedup). What I do is programming the input data, architecture, optimization algorithm, fitness function, etc. Then my pc does the number crunching. The results of each optimization run (several hours to days on my 3Ghz Core2Duo) are often pretty different, so I decided to combine some of them again, to yield a single number for market exposure.
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